CN107608983B

CN107608983B - Title information optimization method, device, equipment and system

Info

Publication number: CN107608983B
Application number: CN201610543485.8A
Authority: CN
Inventors: 吴夙慧; 陈强; 郭立超; 李传福
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2016-07-11
Filing date: 2016-07-11
Publication date: 2021-03-30
Anticipated expiration: 2036-07-11
Also published as: TW201802738A; CN107608983A; WO2018010557A1

Abstract

The application provides a title information optimization method, a title information optimization device, a title information optimization equipment and a title information optimization system, wherein the method comprises the following steps: determining a target business object set to which a business object to be optimized belongs; acquiring a hot vocabulary set corresponding to the target business object set and user characteristics corresponding to the business object to be optimized; determining a target popular vocabulary in the popular vocabulary set according to the user characteristics; and optimizing the title information of the business object to be optimized according to the target popular vocabulary. The method and the device are used for improving the accuracy of recommending the business object to the user.

Description

Title information optimization method, device, equipment and system

Technical Field

The present application relates to the field of internet technologies, and in particular, to a method, an apparatus, a device, and a system for optimizing title information.

Background

Currently, to facilitate distinguishing between different business objects (e.g., merchandise), title information may be determined for the business objects.

In the actual application process, when a user needs to acquire a service object in the data server, the user may search through a search word to acquire a plurality of service objects matched with the search word, specifically: after the data server receives the search word input by the user, the data server usually matches the search word with the title information of each business object to obtain the business object matched with the search word, and recommends the matched business object to the user.

However, since the title information of many business objects is not accurate, the data server cannot recommend an accurate business object to the user according to the title information of the business object.

Disclosure of Invention

The application provides a title information optimization method, a title information optimization device, a title information optimization equipment and a title information optimization system, which are used for improving the accuracy of recommending a service object to a user.

In one aspect, the present application provides a title information optimization method, including:

determining a target business object set to which a business object to be optimized belongs;

acquiring a hot vocabulary set corresponding to the target business object set and user characteristics corresponding to the business object to be optimized;

determining a target popular vocabulary in the popular vocabulary set according to the user characteristics;

and optimizing the title information of the business object to be optimized according to the target popular vocabulary.

In one possible implementation, determining a target topical word in the topical word set based on the user characteristics includes:

acquiring the matching degree of the user characteristics and each popular keyword in the popular keyword set;

and determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword set in the popular keyword set.

In another possible implementation manner, the obtaining the matching degree between the user characteristic and each hit keyword in the hit keyword set includes:

determining a first vocabulary category corresponding to the user characteristics and a second vocabulary category corresponding to each popular keyword;

and determining the matching degree of the data information and each popular keyword according to a preset vocabulary category matching table, the first vocabulary category and each second vocabulary category, wherein the preset vocabulary category matching table comprises the matching degree between each two vocabulary categories.

In another possible implementation manner, the obtaining of the user characteristics corresponding to the service object to be optimized includes:

determining a user to be optimized corresponding to the business object to be optimized;

acquiring user information of the user to be optimized, wherein the user information comprises at least one of registration information of the user to be optimized, additional description information of the user to be optimized and transaction information corresponding to the user to be optimized;

and determining the user characteristics corresponding to the service object to be optimized according to the user information.

In another possible implementation manner, the optimizing the header information of the business object to be optimized according to the target popular vocabulary includes:

And adding the target hot vocabulary to the header information of the business object to be optimized.

In another possible implementation, the adding the target topical vocabulary to the header information of the business object to be optimized includes:

acquiring at least one current keyword included in the title information;

acquiring the weight values of the current keywords and the target popular vocabulary;

determining the position of the target popular vocabulary in the title information according to the weight values of the current keywords and the target popular vocabulary;

and adding the target hot vocabulary to the header information of the business object to be optimized according to the position of the target hot vocabulary in the header information.

sending the target hot vocabulary to a client corresponding to the business object to be optimized so that a user can determine optimized title information according to the target hot vocabulary;

receiving first confirmation header information sent by the client;

and determining the first confirmed header information as the optimized header information of the service object to be optimized.

determining title information to be confirmed according to the title information of the business object to be optimized and the target hot vocabulary;

and sending the title information to be confirmed to a client corresponding to the business object to be optimized so that a user can determine the optimized title information according to the title information to be confirmed.

In another possible implementation manner, the determining, according to the header information of the business object to be optimized and the target popular vocabulary, header information to be confirmed includes:

determining the insertion position of the target hot vocabulary in the header information of the business object to be optimized;

and inserting the target popular vocabulary into the insertion position of the header information to obtain the header information to be confirmed.

In another possible implementation manner, sending the to-be-confirmed header information to a client corresponding to the to-be-optimized service object, so that a user determines the optimized header information according to the to-be-confirmed header information, includes:

sending the title information to be confirmed to a client corresponding to the business object to be optimized;

Receiving confirmation information sent by the client;

and determining the title information to be confirmed as the optimized title information of the business object to be optimized according to the confirmation information.

receiving second confirmation title information sent by the client, wherein the second confirmation title information is obtained by modifying the title to be confirmed by the user;

and determining the second confirmed header information as the optimized header information of the service object to be optimized.

In another possible implementation manner, the determining a target business object set to which a business object to be optimized belongs includes:

acquiring a target category to which a service object to be optimized belongs;

determining a plurality of business object sets to be selected corresponding to the target category;

and determining the target business object set in the plurality of business object sets to be selected.

In another possible implementation manner, the obtaining of the target category to which the to-be-optimized business object belongs includes:

judging whether the business object to be optimized has a category corresponding to the business object to be optimized;

if yes, determining the category corresponding to the service object to be optimized as the target category;

if not, acquiring a first keyword set corresponding to the service object to be optimized, and determining the target category according to the first keyword set and a category prediction model, wherein the category prediction model comprises the corresponding relation between the keywords and the category and the matching degree between the keywords and the category.

In another possible embodiment, the determining the target category according to the first keyword set and a category prediction model includes:

according to the category prediction model, acquiring each keyword in the first keyword set, a category corresponding to the keyword and a matching degree of the keyword;

acquiring the weight value of each keyword in the first keyword set;

and determining the target category according to the weight value of each keyword in the first keyword set and the matching degree between each keyword and the corresponding category.

In another possible implementation manner, determining the target business object set in the multiple candidate business object sets includes:

Judging whether the business object to be optimized has a business object set corresponding to the business object to be optimized;

if yes, determining a service object set corresponding to the service object to be optimized as the target service object set;

if not, acquiring the feature information of the to-be-optimized service object, the feature information of each to-be-selected service object set and the feature similarity between the feature information of the to-be-optimized service object and the feature information of each to-be-selected service object set, and determining a target service object set in the to-be-selected service object set according to the feature similarity between the feature information of the to-be-optimized service object and the feature information of each to-be-selected service object set.

In another possible implementation manner, the determining, according to the feature similarity between the feature information of the optimized service object and the feature information of each candidate service object set, a target service object set in the candidate service object set includes:

determining a to-be-selected business object set with the characteristic similarity larger than the first preset threshold as the target business object set;

or,

and determining N business object sets to be selected with the highest feature similarity as the target business object set, wherein N is a positive integer greater than or equal to 1.

In another possible implementation manner, the obtaining of the feature information of the service object to be optimized includes:

acquiring a first keyword set corresponding to a to-be-optimized business object and a weighted value of each keyword in the first keyword set, acquiring a feature vector of the to-be-optimized business object according to the weighted value of each keyword in the first keyword set, and determining the feature vector of the to-be-optimized business object as feature information of the to-be-optimized business object;

the acquiring the feature information of the to-be-selected business object set includes:

and acquiring the characteristic vector of each service object in the service object set to be selected, determining the central characteristic vector of the service object set to be selected according to the characteristic vector of each service object in the service object set to be selected, and determining the central characteristic vector of the service object set to be selected as the characteristic information of the service object set to be selected.

In another possible implementation manner, the obtaining of the feature similarity between the feature information of the to-be-optimized service object and the feature information of the to-be-selected service object set includes:

and obtaining a cosine included angle between the feature vector of the service object to be optimized and the central feature vector of the service object set to be selected, and determining the feature similarity according to the cosine included angle.

In another possible implementation manner, determining a target business object set in the candidate business object set according to the feature similarity between the feature information of the optimized business object and the feature information of each candidate business object set includes:

respectively acquiring cosine included angles between the feature vectors of the business objects to be optimized and the central feature vectors of all the business object sets to be selected;

and determining a set of the service objects to be selected with cosine included angles smaller than the second preset threshold as the target service object set, or determining the set of the N service objects to be selected with the smallest cosine included angles as the target service object set, wherein the feature similarity corresponding to the cosine included angles with the included angles being the second preset threshold is equal to the first preset threshold.

In another possible implementation manner, the obtaining of the first keyword set corresponding to the to-be-optimized service object includes:

obtaining description information of the business object to be optimized, wherein the description information comprises title information of the business object to be optimized and/or characteristic parameters of the business object to be optimized;

performing word segmentation processing on the description information of the business object to be optimized to obtain a plurality of keywords corresponding to the business object to be optimized and the part of speech of each keyword;

And screening the plurality of keywords according to the part of speech of each keyword to obtain the first keyword set.

In another possible implementation manner, before determining the target business object set to which the business object to be optimized belongs, the method further includes:

acquiring transaction information corresponding to the business object to be optimized;

determining that the transaction information corresponding to the business object to be optimized meets at least one of the following conditions:

the volume of the business object to be optimized in the first preset time is smaller than the volume threshold;

and the click quantity of the business object to be optimized in the second preset time length is smaller than the click quantity threshold value.

In another possible embodiment, before the determining the target category according to the first keyword set and the category prediction model, the method further includes:

acquiring a plurality of search character strings input by a user within a third preset time length, clicked service objects corresponding to the search character strings and the clicked times of the clicked service objects;

acquiring a keyword corresponding to each search character string and a category to which each clicked service object belongs;

and generating a category prediction model according to a plurality of search character strings input within a third preset time length, clicked service objects corresponding to the search character strings, the clicked times of the clicked service objects, keywords corresponding to the search character strings and categories to which the clicked service objects belong.

In another possible implementation manner, the generating a category prediction model according to a plurality of search strings input within a third preset time period, a clicked service object corresponding to each search string, the number of times that each clicked service object is clicked, a keyword corresponding to each belonging search string, and a category to which each clicked service object belongs, includes:

obtaining a first corresponding relation between the search character strings and the clicked service objects according to the identification of the clicked service objects corresponding to the search character strings and the clicked times of the clicked service objects, wherein the first corresponding relation comprises the clicked times of the clicked service objects corresponding to the search character strings;

obtaining a second corresponding relation between the search character string and the category according to the category to which each clicked service object belongs and the first corresponding relation, wherein the second corresponding relation comprises the clicked times of the category corresponding to the search character string;

obtaining a third corresponding relation between the keywords and the categories according to the keywords corresponding to the search character strings and the second corresponding relation, wherein the third corresponding relation comprises the clicked times of the categories corresponding to the keywords;

Generating the matching degree of each keyword and the corresponding category according to the clicked times of the category corresponding to each keyword;

and generating the category prediction model according to the third corresponding relation and the matching degree of the keywords and the categories.

In another possible implementation manner, before the obtaining of the popular vocabulary corresponding to the target business object set, the method further includes:

dividing all the business objects with the same category to obtain a plurality of business object sets, wherein the attribute similarity of the business objects in each business object set is greater than a third preset threshold value, and the plurality of business object sets comprise the target business object set;

respectively acquiring a second keyword set of each business object set to obtain a plurality of second keyword sets;

acquiring a heat value of each keyword in each second keyword set;

and determining a hot vocabulary corresponding to each business object set according to the heat value of each keyword in each second keyword set.

In another possible implementation, the dividing all the service objects of the same category to obtain a plurality of service object sets includes:

acquiring a third keyword set corresponding to each business object with the same category and the weight value of each keyword in the third keyword set;

Acquiring a feature vector of each business object according to the weight value of each keyword in each third keyword set;

and dividing all the service objects with the same category according to the cosine included angle between the characteristic vectors of the service objects to obtain the plurality of service object sets.

In another aspect, the present application provides a title information optimization method, including:

receiving a target hot vocabulary which is sent by a data server and corresponds to a business object to be optimized;

receiving confirmation title information determined by a user according to the title information of the business object to be optimized and the target popular vocabulary;

and sending the confirmation header information to the data server so that the data server optimizes the header information of the business object to be optimized according to the confirmation header information.

In a possible implementation manner, the receiving of the confirmation header information determined by the user according to the header information of the business object to be optimized and the target topical vocabulary includes:

displaying the title information of the business object to be optimized and the target hot vocabulary;

and receiving first confirmation title information input by the user according to the title information and the target popular vocabulary.

In another possible implementation manner, the receiving a target hot vocabulary corresponding to a business object to be optimized, which is sent by a data server, includes:

and receiving to-be-confirmed title information sent by the data server, wherein the to-be-confirmed title information comprises the title information of the to-be-optimized business object and the target popular vocabulary.

In another possible implementation manner, receiving confirmation header information corresponding to the service object to be optimized, which is determined by the user according to the target popular vocabulary, includes:

displaying the title information to be confirmed;

receiving confirmation information which is input by a user and corresponds to the title information to be confirmed;

and determining the title information to be confirmed as the confirmed title information according to the confirmation information.

displaying the title information to be confirmed;

receiving modification operation input by the user on the title information to be confirmed, wherein the modification operation is used for modifying the position of the target popular vocabulary in the title information and/or modifying the vocabulary included in the title information to be confirmed;

And determining second confirmation header information according to the modification operation.

In another possible implementation manner, before the receiving the target popular vocabulary sent by the data server, the method further includes:

receiving title information of a business object to be optimized, which is input by a user;

and sending the title information of the service object to be optimized to a data server, so that the data server determines a target hot vocabulary according to a hot vocabulary set corresponding to a target service object set to which the service object to be optimized belongs and the attribute information of the service object to be optimized.

determining at least one business object set included in the category;

acquiring a first popular vocabulary set corresponding to the category and a second popular vocabulary set corresponding to each business object set;

respectively sending corresponding second popular vocabulary sets to the clients corresponding to the business object sets so that a user can optimize the title information of the business objects in the business object sets according to the second popular vocabulary sets;

and sending the first popular vocabulary set to a client corresponding to the unclassified business object in the category, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first popular vocabulary set.

In a possible implementation manner, obtaining a second popular vocabulary set corresponding to the business object set includes:

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

and determining a second popular vocabulary set corresponding to each business object set according to the heat value of each keyword in the keyword set.

In another possible implementation, obtaining a first popular vocabulary set corresponding to a category includes:

performing deduplication processing on the top keywords in each second top keyword set;

and determining the first popular vocabulary set according to each second popular keyword set subjected to the de-duplication processing.

In another possible implementation manner, the sending a corresponding second popular vocabulary set to a client corresponding to each business object set respectively includes:

determining a client corresponding to each service object in the service object set;

and respectively sending a second popular vocabulary set corresponding to the business object set to the client corresponding to each business object.

In another possible implementation manner, sending the second popular vocabulary set corresponding to the business object set to the client corresponding to each business object respectively includes:

Acquiring user characteristics corresponding to each business object;

determining a target popular vocabulary corresponding to each business object in the second popular vocabulary set according to the user characteristics of each business object;

and respectively sending corresponding target hot vocabularies to each business object.

In another possible implementation, sending the first popular vocabulary set to a client corresponding to an unclassified business object in the category includes:

acquiring the class classification business object included in the class;

determining a client corresponding to each unclassified business object;

and respectively sending the first popular vocabulary set to the client corresponding to each unclassified business object.

receiving a popular vocabulary set sent by a data server;

acquiring the title information of the business object corresponding to the popular vocabulary set;

receiving confirmation title information determined by a user according to the title information of the business object and the popular vocabulary set;

and updating the header information corresponding to the service object into the confirmed header information.

In a possible implementation manner, the receiving user's confirmation header information determined according to the header information of the business object and the popular vocabulary set includes:

Displaying the title information of the business object and the popular vocabulary set;

and receiving confirmation title information input by the user according to the title information and the popular vocabulary set.

In another possible implementation, the popular vocabulary set further includes a weight value of each popular vocabulary; correspondingly, the optimizing the title information of the business object according to the popular vocabulary set includes:

displaying the title information of the business object, the popular vocabulary set and the weight value of each popular vocabulary in the popular vocabulary set;

and receiving confirmation title information input by the user according to the title information, the popular vocabulary set and the weight value of each popular vocabulary.

In another possible implementation, the updating the corresponding header information to the confirmation header information includes:

and sending the confirmation header information and the identification of the service object to the data server so that the data server updates the header information of the service object into the confirmation header information.

In another aspect, the present application provides a title information optimization apparatus, including:

The first determining module is used for determining a target business object set to which a business object to be optimized belongs;

the first acquisition module is used for acquiring a popular vocabulary set corresponding to the target business object set and user characteristics corresponding to the business object to be optimized;

the second determining module is used for determining a target popular vocabulary in the popular vocabulary set according to the user characteristics;

and the optimization module is used for optimizing the title information of the business object to be optimized according to the target popular vocabulary.

In a possible embodiment, the second determination module comprises a first acquisition unit and a first determination unit, wherein,

the first obtaining unit is used for obtaining the matching degree of the user characteristics and each hot keyword in the hot keyword set;

the first determining unit is used for determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword set in the popular keyword set.

In another possible implementation manner, the first obtaining unit is specifically configured to:

In another possible implementation manner, the first obtaining module is specifically configured to:

In another possible implementation, the optimization module is specifically configured to:

acquiring at least one current keyword included in the title information;

In another possible implementation, the optimization module is further specifically configured to:

receiving first confirmation header information sent by the client;

In another possible embodiment, the optimization module comprises a second determination unit and a sending unit, wherein,

the second determining unit is used for determining the title information to be confirmed according to the title information of the business object to be optimized and the target popular vocabulary;

the sending unit is configured to send the to-be-confirmed title information to a client corresponding to the to-be-optimized service object, so that a user determines the optimized title information according to the to-be-confirmed title information.

In another possible implementation manner, the second determining unit is specifically configured to:

In another possible embodiment, the optimization module further comprises a receiving unit and a third determining unit, wherein,

the sending unit is specifically configured to send the to-be-confirmed header information to a client corresponding to the to-be-optimized service object;

the receiving unit is used for receiving the confirmation information sent by the client;

and the third determining unit is configured to determine, according to the confirmation information, the header information to be confirmed as the optimized header information of the service object to be optimized.

In another possible implementation manner, the sending unit is further configured to send the to-be-confirmed header information to a client corresponding to the to-be-optimized service object;

the receiving unit is further configured to receive second confirmation header information sent by the client, where the second confirmation header information is obtained by modifying the title to be confirmed by the user;

The third determining unit is further configured to determine the second confirmation header information as the optimized header information of the service object to be optimized.

In another possible embodiment, the first determining module comprises a second obtaining unit, a fourth determining unit and a fifth determining unit, wherein,

the second obtaining unit is used for obtaining a target category to which the service object to be optimized belongs;

the fourth determining unit is configured to determine a plurality of service object sets to be selected corresponding to the target category;

the fifth determining unit is configured to determine the target business object set in the multiple business object sets to be selected.

In another possible implementation manner, the second obtaining unit is specifically configured to:

acquiring the weight value of each keyword in the first keyword set;

In another possible implementation manner, the fourth determining unit is specifically configured to:

or,

In another possible implementation manner, the second obtaining unit and the fourth determining unit are specifically configured to:

In another possible embodiment, the apparatus further comprises a second obtaining module and a third determining module, wherein,

the second obtaining module is used for obtaining the transaction information corresponding to the business object to be optimized before the first determining module determines the target business object set to which the business object to be optimized belongs;

the third determining module is configured to determine that the transaction information corresponding to the to-be-optimized business object meets at least one of the following conditions:

In another possible implementation manner, the apparatus further includes a third obtaining module, a fourth obtaining module, and a generating module, wherein,

the third obtaining module is configured to, before the second obtaining unit determines the target category according to the first keyword set and the category prediction model, obtain a plurality of search strings input by a user within a third preset duration, a clicked service object corresponding to each search string, and the number of times of clicking of each clicked service object;

The fourth obtaining module is configured to obtain a keyword corresponding to each search string and a category to which each clicked service object belongs;

the generation module is used for generating a category prediction model according to a plurality of search character strings input within a third preset time length, clicked service objects corresponding to the search character strings, the clicked times of the clicked service objects, keywords corresponding to the search character strings and categories to which the clicked service objects belong.

In another possible implementation manner, the generating module is specifically configured to:

In another possible implementation manner, the apparatus further includes a dividing module, a fifth obtaining module, and a fourth determining module, wherein,

the dividing module is used for dividing all the business objects with the same category to obtain a plurality of business object sets before the second obtaining unit obtains the hot vocabulary corresponding to the target business object set, wherein the attribute similarity of the business objects in each business object set is greater than a third preset threshold value, and the plurality of business object sets comprise the target business object set;

the fifth obtaining module is configured to obtain a second keyword set of each service object set, obtain a plurality of second keyword sets, and obtain a heat value of each keyword in each second keyword set;

And the fourth determining module is used for determining the hot vocabulary corresponding to each business object set according to the heat value of each keyword in each second keyword set.

In another possible implementation manner, the dividing module is specifically configured to:

the first receiving module is used for receiving a target hot vocabulary which is sent by the data server and corresponds to the business object to be optimized;

the second receiving module is used for receiving the confirmed title information determined by the user according to the title information of the business object to be optimized and the target popular vocabulary;

and the sending module is used for sending the confirmed title information to the data server so that the data server optimizes the title information of the service object to be optimized according to the confirmed title information.

In a possible embodiment, the device further comprises a display module, wherein,

the display module is used for displaying the title information of the business object to be optimized and the target popular vocabulary;

correspondingly, the second receiving module is used for receiving first confirmation title information input by the user according to the title information and the target popular vocabulary.

In another possible implementation manner, the first receiving module is specifically configured to:

In another possible implementation manner, the display module is further configured to display the title information to be confirmed;

correspondingly, the second receiving module is specifically configured to receive confirmation information corresponding to the to-be-confirmed title information and input by a user, and determine the to-be-confirmed title information as the confirmation title information according to the confirmation information.

Correspondingly, the second receiving module is specifically configured to receive a modification operation input by the user on the to-be-confirmed header information, where the modification operation is used to modify a position of the target popular vocabulary in the header information and/or modify the vocabulary included in the to-be-confirmed header information, and determine second confirmed header information according to the modification operation.

In another possible implementation manner, the second receiving module is further configured to receive, before the first receiving module receives the target popular vocabulary sent by the data server, header information of the business object to be optimized, which is input by the user;

correspondingly, the sending module is further configured to send the header information of the service object to be optimized to the data server, so that the data server determines a target hot vocabulary according to a hot vocabulary set corresponding to a target service object set to which the service object to be optimized belongs and the attribute information of the service object to be optimized.

a determining module, configured to determine at least one business object set included in the category;

the acquisition module is used for acquiring a first popular vocabulary set corresponding to the category and a second popular vocabulary set corresponding to each business object set;

The sending module is used for respectively sending corresponding second popular vocabulary sets to the clients corresponding to the business object sets so that a user can optimize the title information of the business objects in the business object sets according to the second popular vocabulary sets;

the sending module is further configured to send the first popular vocabulary set to a client corresponding to an unclassified business object in the category, where the unclassified business object does not belong to any business object set in the category, so that a user optimizes title information of the unclassified business object according to the first popular vocabulary set.

In a possible implementation manner, the obtaining module is specifically configured to:

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

In another possible implementation manner, the obtaining module is specifically configured to:

In another possible embodiment, the sending module comprises a determining unit and a sending unit, wherein,

the determining unit is used for determining the client corresponding to each service object in the service object set;

and the sending unit is used for sending the second popular vocabulary sets corresponding to the business object sets to the clients corresponding to the business objects respectively.

In another possible implementation manner, the sending unit is specifically configured to:

acquiring user characteristics corresponding to each business object;

In another possible implementation manner, the sending module is specifically configured to:

acquiring the class classification business object included in the class;

determining a client corresponding to each unclassified business object;

the first receiving module is used for receiving the popular vocabulary set sent by the data server;

the acquisition module is used for acquiring the title information of the business object corresponding to the popular vocabulary set;

the second receiving module is used for receiving the confirmed title information determined by the user according to the title information of the business object and the popular vocabulary set;

and the updating module is used for updating the title information corresponding to the business object into the confirmed title information.

the display module is used for displaying the title information of the business object and the popular vocabulary set;

correspondingly, the second receiving module is used for receiving the confirmation title information input by the user according to the title information and the popular vocabulary set.

In another possible implementation, the popular vocabulary set further includes a weight value of each popular vocabulary;

correspondingly, the display module is used for displaying the title information of the business object, the popular vocabulary set and the weight value of each popular vocabulary in the popular vocabulary set;

The second receiving module is used for receiving the confirmation title information input by the user according to the title information, the popular vocabulary set and the weight value of each popular vocabulary.

In another possible implementation manner, the update module is specifically configured to:

In another aspect, the present application provides a data server, including a processor and a memory for storing an application program, where the processor is configured to read the application program in the memory and perform the following operations:

In one possible implementation, the processor is specifically configured to:

In another possible implementation, the processor is specifically configured to:

In another possible implementation manner, the processor is specifically configured to add the target topical vocabulary to the header information of the business object to be optimized.

acquiring at least one current keyword included in the title information;

receiving first confirmation header information sent by the client;

In another possible implementation, the data server further includes a communication port, wherein the processor is specifically configured to:

and sending the title information to be confirmed to a client corresponding to the service object to be optimized through the communication port so that a user can determine the optimized title information according to the title information to be confirmed.

sending the title information to be confirmed to a client corresponding to the business object to be optimized through the communication port;

receiving confirmation information sent by the client;

acquiring a target category to which a service object to be optimized belongs;

In another possible implementation, the processor is specifically configured to: judging whether the business object to be optimized has a category corresponding to the business object to be optimized;

acquiring the weight value of each keyword in the first keyword set;

or,

In another possible implementation, the processor is further configured to:

before the processor determines a target business object set to which a business object to be optimized belongs, acquiring transaction information corresponding to the business object to be optimized;

In another possible implementation, the processor is further configured to:

before the second obtaining unit determines the target category according to the first keyword set and the category prediction model, obtaining a plurality of search character strings input by a user within a third preset time length, clicked service objects corresponding to the search character strings, and clicked times of the clicked service objects;

In another possible implementation, the processor is further configured to:

before the processor obtains a hot vocabulary corresponding to a target business object set, dividing all business objects with the same category to obtain a plurality of business object sets, wherein the attribute similarity of the business objects in each business object set is greater than a third preset threshold value, and the plurality of business object sets comprise the target business object set;

respectively acquiring a second keyword set of each business object set to obtain a plurality of second keyword sets, and acquiring the heat value of each keyword in each second keyword set;

In another possible implementation, the processor is specifically configured to: acquiring a third keyword set corresponding to each business object with the same category and the weight value of each keyword in the third keyword set;

In another aspect, the present application provides a client comprising a processor, a communication port, an input device, and a memory for storing an application program, wherein,

the processor is used for receiving a target hot vocabulary corresponding to the business object to be optimized, which is sent by the data server, through the communication port;

the input equipment is used for receiving confirmation title information determined by a user according to the title information of the business object to be optimized and the target popular vocabulary;

the processor is further configured to send the confirmation header information to the data server through the communication port, so that the data server optimizes the header information of the to-be-optimized service object according to the confirmation header information.

In one possible implementation, the client further comprises a display device, wherein,

the display equipment is used for displaying the title information of the business object to be optimized and the target hot vocabulary;

Correspondingly, the input device is specifically configured to receive first confirmation header information input by the user according to the header information and the target popular vocabulary.

In another possible implementation manner, the processor is specifically configured to receive, through the communication port, to-be-confirmed header information sent by the data server, where the to-be-confirmed header information includes header information of the to-be-optimized business object and the target popular vocabulary.

In another possible implementation manner, the display device is further configured to display the title information to be confirmed;

correspondingly, the input device is specifically configured to receive confirmation information corresponding to the title information to be confirmed, which is input by a user;

the processor is specifically configured to determine, according to the confirmation information, the header information to be confirmed as the confirmation header information.

correspondingly, the input device is specifically configured to receive a modification operation input by the user on the to-be-confirmed header information, where the modification operation is used to modify a position of the target popular vocabulary in the header information and/or modify a vocabulary included in the to-be-confirmed header information;

The processor is specifically configured to determine second acknowledgment header information based on the modify operation.

In another possible embodiment, the processor is further configured to receive, through the communication port, header information of a business object to be optimized, which is input by a user, before the processor receives, through the communication port, a target popular vocabulary sent by the data server;

correspondingly, the processor is specifically configured to send header information of the to-be-optimized service object to a data server through the communication port, so that the data server determines a target hot vocabulary according to a hot vocabulary set corresponding to a target service object set to which the to-be-optimized service object belongs and attribute information of the to-be-optimized service object.

In another aspect, the present application provides a data server, including a processor, a communication port, and a memory for storing an application program, where the processor is configured to read the application program in the memory and perform the following operations:

determining at least one business object set included in the category;

Respectively sending corresponding second hot vocabulary sets to the clients corresponding to the business object sets through the communication ports so that a user can optimize the title information of the business objects in the business object sets according to the second hot vocabulary sets;

and sending the first popular vocabulary set to a client corresponding to the unclassified business object in the category through the communication port, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first popular vocabulary set.

In one possible implementation, the processor is specifically configured to:

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

and respectively sending a second popular vocabulary set corresponding to the business object set to the client corresponding to each business object through the communication port.

acquiring user characteristics corresponding to each business object;

and respectively sending corresponding target hot words to each business object through the communication port.

acquiring the class classification business object included in the class;

determining a client corresponding to each unclassified business object;

and respectively sending the first popular vocabulary set to the client corresponding to each unclassified business object through the communication port.

the processor is used for receiving the popular vocabulary set sent by the data server through the communication port;

the processor is further configured to obtain header information of the business object corresponding to the popular vocabulary set;

the input equipment is used for receiving confirmation title information determined by a user according to the title information of the business object and the popular vocabulary set;

the processor is further configured to update the header information corresponding to the service object to the confirmation header information.

the display equipment is used for displaying the title information of the business object and the popular vocabulary set;

correspondingly, the input device is specifically configured to receive confirmation header information input by the user according to the header information and the popular vocabulary set.

correspondingly, the display device is used for displaying the title information of the business object, the popular vocabulary set and the weight value of each popular vocabulary in the popular vocabulary set;

The input device is specifically configured to receive confirmation header information input by the user according to the header information, the popular vocabulary sets, and the weight values of the popular vocabularies.

In another aspect, the present application provides a title information optimization system, comprising a data server and a client, wherein,

the data server is used for determining a target business object set to which a business object to be optimized belongs, acquiring a hot vocabulary set corresponding to the target business object set and user characteristics corresponding to the business object to be optimized, determining a target hot vocabulary in the hot vocabulary set according to the user characteristics, and sending the target hot vocabulary to a client;

the client is used for receiving the target hot words corresponding to the to-be-optimized service object sent by the data server, receiving confirmation header information determined by a user according to the header information of the to-be-optimized service object and the target hot words, and sending the confirmation header information to the data server, so that the data server optimizes the header information of the to-be-optimized service object according to the confirmation header information.

the data server is used for determining at least one service object set included in the category, acquiring a first hot vocabulary set corresponding to the category and a second hot vocabulary set corresponding to each service object set, respectively sending the corresponding second hot vocabulary sets to the clients corresponding to each service object set, and sending the first hot vocabulary sets to the clients corresponding to the unclassified service objects in the category;

the client is used for receiving the hot vocabulary set sent by the data server, acquiring the title information of the business object corresponding to the hot vocabulary set, receiving the confirmation title information determined by the user according to the title information of the business object and the hot vocabulary set, and updating the title information corresponding to the business object into the confirmation title information.

In the application, when the title information optimization device needs to optimize the title information of the service object to be optimized, the title information optimization device determines a target service object set corresponding to the service object to be optimized, determines a target hot word in a hot word set corresponding to the target service object set according to the user characteristics corresponding to the service object to be optimized, and optimizes the title information of the service object to be optimized according to the target hot word. In the process, the attribute similarity between the service object to be optimized and the service object in the target service object set is high, so that the matching degree between the hot vocabulary set of the target service object set and the service object to be optimized is high, and further, the target hot vocabulary is determined according to the user characteristics corresponding to the service object to be optimized and the hot vocabulary set of the target service object set, so that the characteristic information of the service object to be optimized can be better embodied by the target hot vocabulary, and therefore, the header information of the service object to be optimized can be accurately optimized through the target hot vocabulary, and the accuracy of recommending the service object to the user by the data server is further improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 is a schematic view of an application scenario of a title information optimization method provided by the present invention;

FIG. 2 is a first flowchart of a title information optimization method provided by the present invention;

FIG. 3 is a diagram of a business object management architecture provided by the present invention;

FIG. 4 is a flowchart illustrating a method for determining a target popular vocabulary according to the present invention;

FIG. 5 is a first flowchart illustrating a method for optimizing heading information according to a target topical vocabulary according to the present invention;

FIG. 6 is a flowchart illustrating a second method for optimizing heading information according to a target topical vocabulary according to the present invention;

FIG. 7 is a flowchart illustrating a method for optimizing heading information according to a target popular vocabulary according to the present invention;

FIG. 8 is a flowchart of a method for determining a set of target business objects according to the present invention;

FIG. 9 is a flowchart of a method for obtaining target categories provided by the present invention;

FIG. 10 is a flowchart of a method for obtaining a first keyword set according to the present invention;

FIG. 11 is a flow chart of a method for determining a target category based on a category prediction model provided by the present invention;

FIG. 12 is a flowchart of a method for determining a set of target business objects according to the present invention;

FIG. 13 is a flow chart of a method for generating a category prediction model provided by the present invention;

FIG. 14 is a flowchart of a method for generating popular vocabulary corresponding to a set of business objects according to the present invention;

FIG. 15 is a second flowchart of a title information optimization method provided by the present invention;

FIG. 16 is a first flowchart illustrating a method for acquiring confirmed header information according to the present invention;

FIG. 17 is a first schematic diagram of a client interface provided by the present invention;

FIG. 18 is a flowchart illustrating a second method for acquiring confirmed header information according to the present invention;

FIG. 19 is a second schematic diagram of a client interface provided by the present invention;

FIG. 20 is a flowchart of a third method for acquiring confirmed header information according to the present invention;

FIG. 21 is a third schematic diagram of a client interface provided by the present invention;

FIG. 22 is a flowchart III of the title information optimization method provided by the present invention;

FIG. 23 is a fourth flowchart of a title information optimization method provided by the present invention;

FIG. 24 is a fifth flowchart of a title information optimization method provided by the present invention;

FIG. 25 is a first schematic structural diagram of a title information optimization apparatus according to the present invention;

FIG. 26 is a second schematic structural diagram of a title information optimization apparatus according to the present invention;

FIG. 27 is a first schematic structural diagram of another title information optimization apparatus provided in the present invention;

FIG. 28 is a second schematic structural diagram of another title information optimization apparatus provided in the present invention;

FIG. 29 is a first schematic structural diagram of another title information optimization apparatus according to the present invention;

FIG. 30 is a second schematic structural diagram of another title information optimization apparatus according to the present invention;

FIG. 31 is a first schematic structural diagram of a further apparatus for optimizing header information according to the present invention;

FIG. 32 is a second schematic structural diagram of a header information optimizing apparatus according to another embodiment of the present invention;

FIG. 33 is a first schematic structural diagram of a data server according to the present invention;

fig. 34 is a schematic structural diagram of a data server according to the present invention;

fig. 35 is a first schematic structural diagram of a client according to the present invention;

fig. 36 is a schematic structural diagram of a client according to the present invention;

FIG. 37 is a block diagram of another data server provided by the present invention;

Fig. 38 is a first schematic structural diagram of another client according to the present invention;

fig. 39 is a schematic structural diagram of another client according to the present invention;

FIG. 40 is a schematic structural diagram of a system for optimizing header information according to the present invention;

fig. 41 is a schematic structural diagram of another title information optimization system provided in the present invention.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.

Fig. 1 is a schematic view of an application scenario of the title information optimization method provided by the present invention, please refer to fig. 1, which includes a client 101 and a data server 102. The client 101 may be a computer, a mobile phone, or other devices. The user can input the title information of the business object to be optimized at the client 101, and send the title information of the business object to be optimized to the data server 102 through the client 101. The data server 102 may optimize the title information of the service object to be optimized, so that the title information of the service object to be optimized is more accurate, and the accuracy of recommending the service object to the user by the data server is further improved. The technical means shown in the present application will be described in detail below with reference to specific examples.

It should be noted that the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

Fig. 2 is a first flowchart of a title information optimization method provided by the present invention, please refer to fig. 2, which may include:

s201, determining a target business object set to which a business object to be optimized belongs;

s202, acquiring a hot vocabulary set corresponding to a target business object set and user characteristics corresponding to a business object to be optimized;

s203, determining a target popular vocabulary in the popular vocabulary set according to the user characteristics;

and S204, optimizing the title information of the business object to be optimized according to the target popular vocabulary.

The execution subject of the embodiment of the present invention may be a title information optimization apparatus, which may be implemented by software and/or hardware. The title information optimizing means may be provided in the data server.

To facilitate understanding of the scheme of the embodiment of the present invention, first, a method for managing a business object by a title information optimization apparatus is described with reference to fig. 3.

Fig. 3 is a diagram of a business object management architecture provided by the present invention, and please refer to fig. 3, in order to facilitate management of business objects, a plurality of categories may be provided. Each category may include a plurality of service object sets, each service object set includes a plurality of service objects, and attribute information of all service objects in one service object set is the same or similar. Optionally, when the user needs to add a new service object, the user may select a category matching the service object from the multiple categories, or the header information optimization device may automatically select a matching category for the service object. Of course, if neither the user nor the title information optimization apparatus selects a matching category for the newly added service object in time, the service object does not belong to any category, for example, the service object a, the service object B, the service object O, the service object R, and the like shown in fig. 3. In the actual application process, the header information optimization apparatus may periodically classify the service objects having the same or similar attribute information in the same category to obtain a plurality of service object sets in the same category, and certainly, when a new service object is added, if the header information optimization apparatus does not classify the service objects in the same category in time, it may be possible that a service object in a category does not belong to any service object set, for example, the service object T shown in fig. 3.

In the actual application process, when the title information optimization device needs to optimize the title information of the service object to be optimized, the title information optimization device firstly determines a target service object set corresponding to the service object to be optimized in all service object sets of the data server. The target business object set may be one business object set or a plurality of business object sets. The service object sets except the target service object set in all the service object sets of the data server are non-target service sets, and the attribute similarity of the target service object set and the service object to be optimized is greater than the attribute similarity of the non-target service object set and the service object to be optimized.

After the title information optimization device determines to obtain a target business object set corresponding to a business object to be optimized, the title information optimization device obtains a hot vocabulary set corresponding to the target business object set. The hot vocabulary set can accurately reflect the characteristics of the target business object set. Optionally, the popular vocabulary set may be determined according to actual searching and viewing conditions of the user on the business objects in the target business object set.

The title information optimization device further obtains a user characteristic corresponding to the business object to be optimized, where the user characteristic is used to represent characteristic information of a user corresponding to the business object to be optimized, for example, the user characteristic may be a style, a seniority, and the like of the user corresponding to the business object to be optimized. Optionally, the title information optimizing apparatus may determine a user to be optimized corresponding to the service object to be optimized, and obtain user information of the user to be optimized, where the user information may include at least one of registration information of the user to be optimized, additional description information of the user to be optimized, and transaction information corresponding to the user to be optimized, and determine user characteristics corresponding to the service object to be optimized according to the user information.

After the title information optimization device obtains the hot vocabulary set corresponding to the target business object set and the user characteristics corresponding to the business object to be optimized, the title information optimization device determines the target hot vocabulary in the hot vocabulary set according to the user characteristics and optimizes the title information of the business object to be optimized according to the target hot vocabulary. The target topical vocabulary may be a topical vocabulary that matches the user characteristics.

The method shown in the embodiment of fig. 2 is described in detail below by way of specific examples.

For example, assuming that the current title information of the business object 1 is "spring skirt", when the title information optimization apparatus needs to optimize the title information of the business object 1, the title information optimization apparatus determines a target business object set corresponding to the business object 1, and assumes that the target business object set is the business object set 1.

The title information optimization device acquires a hot vocabulary set 1 of a business object set 1, and the hot vocabulary set 1 is assumed to be: "2016", "one-piece dress", "Korean edition", "gentlewoman", "European and American", "personality". The title information optimization device also obtains the user characteristics of the business object 1, and the user characteristics of the business object 1 are assumed to be 'personality'.

The title information optimization device acquires a target popular vocabulary matched with the user characteristics (personality) of the business object 1 from the popular vocabulary set 1: "2016", "Europe and America" and "personality", and add target popular vocabulary ("2016", "Europe and America" and "personality") to the current title information, and the optimized title information is: "spring skirt 2016 European personality".

On the basis of the embodiment shown in fig. 2, alternatively, the target topical vocabulary in the topical vocabulary set may be determined according to the user characteristics through the following feasible implementation manner (S203 in the embodiment shown in fig. 2), specifically, please refer to the embodiment shown in fig. 4.

Fig. 4 is a flowchart illustrating a method for determining a target popular vocabulary according to the present invention, referring to fig. 4, the method may include:

s401, obtaining the matching degree of the user characteristics and each hot keyword in the hot keyword set;

s402, determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword set in the popular keyword set.

In the embodiment shown in fig. 4, when the title information optimization apparatus needs to determine a target popular vocabulary in a popular vocabulary set corresponding to a target business object, the title information optimization apparatus first obtains a matching degree between a user characteristic and each popular keyword set in the popular keyword set; optionally, the title information optimizing apparatus may determine a first vocabulary category corresponding to the user characteristic and a second vocabulary category corresponding to each popular keyword, and determine a matching degree between the data information and each popular keyword according to a preset vocabulary category matching table, the first vocabulary category and each second vocabulary category, where the preset vocabulary category matching table includes a matching degree between each two vocabulary categories. Optionally, the preset vocabulary category matching table may be as shown in table 1:

TABLE 1

Class of vocabulary	Class of vocabulary	Degree of matching
			Vocabulary category 1	Vocabulary category 2	80％
Vocabulary category 1	Vocabulary category 3	68％
			Vocabulary category 1	Vocabulary category 4	95％
Vocabulary category 2	Vocabulary category 3	60％
			Vocabulary category 2	Vocabulary category 4	90％
……	……	……

After the title information optimization device obtains the matching degree of the user characteristics and each hot keyword in the hot keyword set, determining a target hot word in the hot word set according to the matching degree of the user characteristics and each hot keyword in the hot keyword set. Optionally, the title information optimizing apparatus may determine, as the target popular vocabulary, X popular vocabularies with the highest degree of matching with the user characteristics, where X is a positive integer greater than or equal to 1, and in an actual application process, the size of X may be set according to actual needs. Of course, the title information optimization apparatus may also determine a popular vocabulary with a matching degree with the user characteristics greater than a preset threshold as the target popular vocabulary.

On the basis of any one of the above embodiments, after the title information optimization device determines to obtain the target popular vocabulary, the title information of the business object to be optimized can be optimized through various feasible implementation manners. In the following, three possible implementations are described by the embodiments shown in fig. 5-7, wherein in the embodiment shown in fig. 5, the title information optimization device directly optimizes the title information; in the embodiments shown in fig. 6 to 7, the title information optimization device performs optimization on the title information by interacting with the client; specifically, please refer to the embodiments shown in fig. 5-6.

Fig. 5 is a first flowchart of a method for optimizing heading information according to a target topical vocabulary according to the present invention, referring to fig. 5, the method may include:

s501, acquiring at least one current keyword included in the title information;

s502, acquiring the weight values of each current keyword and a target popular vocabulary;

s503, determining the position of the target popular vocabulary in the title information according to the current keywords and the weight value of the target popular vocabulary;

s504, according to the position of the target hot vocabulary in the header information, adding the target hot vocabulary to the header information of the business object to be optimized.

In the embodiment shown in fig. 5, the title information optimization apparatus adds the target hot vocabulary to the title information of the business object to be optimized, specifically:

the title information optimization device obtains at least one current keyword included in the title information of the service object to be optimized, and optionally, the title information optimization device may perform word segmentation processing on the title information of the service object to be optimized to obtain the at least one current keyword.

The title information optimization device also acquires the weight values of the current keywords and the target popular vocabulary, and determines the position of the target popular vocabulary in the title information according to the weight values of the current keywords and the target popular vocabulary. Optionally, the title information optimizing apparatus may determine a corresponding weight value according to the heat value of each current keyword and the target popular vocabulary, where the higher the heat value is, the higher the weight value is. Optionally, the higher the weight value of the target topical word is, the more forward the position of the target topical word in the header information is.

The method shown in the embodiment of fig. 5 will be described in detail below by specific examples.

For example, suppose the title information of the business object to be optimized is "spring skirt long style", and then suppose the target hot vocabulary is: "2016" and "personality".

The title information optimizing device performs word segmentation processing on the title information "spring skirt long style" to obtain current keywords "spring", "skirt" and "long style", and the title information optimizing device obtains the weight values of each current keyword and each target popular vocabulary, as shown in table 2:

TABLE 2

Current keyword or target hot vocabulary	Weighted value
		Spring season	7
Skirt	6
		Long money	4
2016	8
		Personality	5

After the title information optimizing device obtains the weight values of each current keyword and each target popular vocabulary shown in table 2, the title information optimizing device determines the position of each target popular vocabulary in the title information, optionally, the title information optimizing device sequences the sequence positions of the current keyword and the target popular vocabulary in sequence according to the sequence from high to low of the weight values, and the obtained optimized title information is '2016 spring skirt individual long money'.

In the actual application process, when the data server matches the search word with the title information of the service object, the data server usually matches the search word in sequence according to the sequence of the keywords in the title information from front to back; through the embodiment shown in fig. 5, the title information optimization device adds the target topical vocabulary to the corresponding position of the title information according to the weight values of each current keyword and the target topical vocabulary, so that the optimized title information is more accurate, and the accuracy of recommending the service object to the user by the data server is further improved.

Fig. 6 is a second flowchart of a method for optimizing heading information according to a target topical vocabulary according to the present invention, referring to fig. 6, the method may include:

s601, sending a target hot vocabulary to a client corresponding to a business object to be optimized so that a user can determine optimized title information according to the target hot vocabulary;

s602, receiving first confirmation header information sent by a client;

s603, determining the first confirmed title information as the optimized title information of the service object to be optimized.

In the embodiment shown in fig. 6, after the title information optimization device determines that the target topical vocabulary is obtained, the title information optimization device sends the target topical vocabulary to the client corresponding to the business object to be optimized, so that the user determines the optimized title information according to the target topical vocabulary.

After a user determines to obtain first confirmation title information according to the target popular vocabulary at the client, the first confirmation title information is sent to the title information optimization device through the client, and the title information optimization device determines the first confirmation title information as the optimized title information of the service object to be optimized.

In the process, the title information optimization device sends the target hot vocabulary to the client, and the user determines the optimized title information according to the target hot vocabulary at the client, so that the flexibility of optimizing the title information is improved.

Fig. 7 is a flowchart of a third method for optimizing heading information according to a target popular vocabulary according to the present invention, referring to fig. 7, the method may include:

s701, determining title information to be confirmed according to the title information of the business object to be optimized and the target hot vocabulary;

s702, sending the title information to be confirmed to the client corresponding to the business object to be optimized so that the user can determine the optimized title information according to the title information to be confirmed.

In the embodiment shown in fig. 7, after the header information optimizing device determines to obtain the target popular vocabulary, the header information optimizing device first determines to-be-confirmed header information according to the header information of the to-be-optimized service object and the target popular vocabulary, specifically, determines the insertion position of the target popular vocabulary in the header information of the to-be-optimized service object, and inserts the target popular vocabulary in the insertion position of the header information to obtain the to-be-confirmed header information. It should be noted that the header information optimizing apparatus may determine to obtain the header information to be confirmed according to the method shown in the embodiment of fig. 5, which is not described again in the present invention.

After the title information optimizing device determines to-be-confirmed title information, the title information optimizing device sends the to-be-confirmed title information to a client corresponding to the to-be-optimized business object, so that a user determines the optimized title information according to the to-be-confirmed title information. Optionally, after the client receives the header information to be confirmed, the user may confirm the header information to be confirmed, or modify the header information to be confirmed, specifically:

If the user approves the title information to be confirmed, the client can send confirmation information to the title information optimization device, so that the title information optimization device determines the title information to be confirmed as the optimized title information of the business object to be optimized according to the confirmation information.

If the user does not approve the title information to be confirmed, the user can modify the title information to be confirmed to obtain second confirmed title information, and the second confirmed title information is sent to the title information optimization device, so that the title information optimization device determines the second confirmed title information as the optimized title information of the service object to be optimized.

In the process, the title information optimizing device firstly determines the title information to be confirmed according to the target popular vocabulary, and the user determines the optimized title information according to the title information to be confirmed, so that the flexibility of optimizing the title information is further improved.

On the basis of the foregoing embodiment, in order to increase the speed at which the header information optimization device determines to obtain the target service object set, the target service object set corresponding to the service object to be optimized may be determined in the following feasible implementation manner (S201 in the embodiment shown in fig. 2), specifically, please refer to the embodiment shown in fig. 8.

Fig. 8 is a flowchart of a method for determining a target business object set according to the present invention, please refer to fig. 8, where the method may include:

s801, acquiring a target category to which a service object to be optimized belongs;

s802, determining a plurality of service object sets to be selected corresponding to the target category;

s803, a target business object set is determined in the multiple business object sets to be selected.

In the embodiment shown in fig. 8, in order to quickly obtain the target service object set corresponding to the service object to be optimized, the header information optimization device may first obtain a target category to which the service object to be optimized belongs, and obtain a plurality of service object sets to be selected corresponding to the target category. Optionally, a corresponding relationship between the category and the service object set may be set, so that the title information optimization apparatus may determine a plurality of service object sets to be selected corresponding to the target category according to the target category and the corresponding relationship. After the title information optimization device determines a plurality of candidate service object sets, the title information optimization device determines a target service object set in the plurality of candidate service object sets, specifically, the title information optimization device determines a target service object set according to the attribute similarity between each candidate service object set in the plurality of candidate service object sets and the target service object set, determining one or more business object sets with higher similarity with the target business object attribute as a target business object set in a plurality of candidate business object sets, optionally, N business object sets (N is a positive integer greater than or equal to 1) with the highest similarity to the attributes of the candidate business object sets may be determined as the target business object set, or, determining the service object set with the attribute similarity greater than a first preset threshold with the service object set to be selected as a target service object set.

In the process, the target category to which the service object to be optimized belongs is obtained first, and the target service object set is determined in the plurality of service object sets to be selected corresponding to the target category, so that the range of the title information optimization device for selecting the target service object set is narrowed, and the speed of the title information optimization device for determining the target service object set is increased.

On the basis of the embodiment shown in fig. 8, optionally, the title information optimization apparatus may obtain the target category to which the service object to be optimized belongs through the following feasible implementation manner (S801 in the embodiment shown in fig. 8), specifically, please refer to the embodiment shown in fig. 9.

Fig. 9 is a flowchart of a method for obtaining a target category according to the present invention, referring to fig. 9, the method may include:

s901, judging whether the business object to be optimized has a category corresponding to the business object to be optimized;

if yes, executing S902;

if not, executing S903-S904;

s902, determining the category corresponding to the service object to be optimized as a target category;

s903, acquiring a first keyword set corresponding to a business object to be optimized;

and S904, determining a target category according to the first keyword set and the category prediction model, wherein the category prediction model comprises the corresponding relation between the keywords and the category and the matching degree between the keywords and the category.

As can be seen from the management architecture diagram of the business objects shown in fig. 3, part of the business objects are already classified under the category to which they belong, and part of the business objects are not classified under the category to which they belong, so that, when it is necessary to determine the target category to which the business object to be optimized belongs, the title information optimization apparatus first determines whether the business object to be optimized has the category corresponding to it:

if the category exists, it indicates that the service object to be optimized is classified into the category to which the service object belongs, the title information optimization device may directly determine the category corresponding to the service object to be optimized as the target category.

If the keyword does not exist in the list, the title information optimization device needs to acquire a first keyword set corresponding to a service object to be optimized and a preset category prediction model, where the category prediction model includes a corresponding relationship between the keyword and the category and a matching degree between the keyword and the category, where the matching degree between the keyword and the category refers to a probability that the service object corresponding to the keyword is divided into the categories, one keyword may correspond to one or more categories, and one category may also correspond to one or more keywords, and optionally, the category prediction model may be as shown in table 3:

TABLE 3

After the title information optimization device obtains the first keyword set and the category prediction model, determining a target category corresponding to the service object to be optimized according to the first keyword set and the category prediction model.

For further details of the embodiment shown in fig. 9, the following respectively describes the processes of obtaining the first keyword set corresponding to the service object to be optimized and determining the target class corresponding to the service object to be optimized according to the first keyword set and the class prediction model by the embodiments shown in fig. 10 to 11.

Fig. 10 is a flowchart of a method for obtaining a first keyword set according to the present invention, please refer to fig. 10, where the method may include:

s1001, obtaining description information of a business object to be optimized, wherein the description information comprises title information of the business object to be optimized and/or characteristic parameters of the business object to be optimized;

s1002, performing word segmentation processing on the description information of the business object to be optimized to obtain a plurality of keywords corresponding to the business object to be optimized and the part of speech of each keyword;

s1003, screening the plurality of keywords according to the part of speech of each keyword to obtain a first keyword set.

In the embodiment shown in fig. 10, when the title information optimization device needs to obtain the first keyword set corresponding to the service object to be optimized, the title information optimization device obtains service object description information of the service object to be optimized, where the service object description information includes title information of the service object to be optimized and/or a feature parameter of the service object to be optimized, where the feature parameter of the service object to be optimized is attribute information of the service object to be optimized, such as a brand of the service object to be optimized, a manufacturer of the service object to be optimized, a place of production of the service object to be optimized, and the feature parameter may be provided by a user corresponding to the service object to be optimized.

After the title information optimization device obtains the description information of the service object to be optimized, the title information optimization device performs word segmentation processing on the description information of the service object to be optimized to obtain a plurality of keywords corresponding to the service object to be optimized and the part of speech of each keyword, wherein the part of speech comprises nouns, adjectives, adverbs, auxiliary words and the like, then the title information optimization device performs screening processing on the plurality of keywords according to the part of speech of each keyword to obtain a first keyword set, optionally, when the plurality of keywords are screened, the keywords with the part of speech being nouns or adjectives can be reserved, and the keywords with the part of speech being auxiliary words or auxiliary words can be deleted.

For example, assuming that the description information of the service object to be optimized is a "one-piece dress comfortable in spring," when the title information optimization apparatus needs to obtain the first keyword set of the service object to be optimized, the title information optimization apparatus first performs word segmentation on the description information to obtain the following multiple keywords and parts of speech of each keyword: the title information optimizing device comprises a first keyword set, a second keyword set and a third keyword set, wherein the first keyword set comprises a first keyword set and a second keyword set, the second keyword set comprises a first keyword set and a second keyword set, the first keyword set comprises a first keyword set, the first keyword set comprises: "spring", "comfortable" and "one-piece dress".

Fig. 11 is a flowchart of a method for determining a target category according to a category prediction model provided in the present invention, please refer to fig. 11, where the method may include:

s1101, obtaining each keyword in the first keyword set, the category corresponding to the keyword and the matching degree according to the category prediction model;

s1102, acquiring a weight value of each keyword in the first keyword set;

s1103, determining a target category according to the weight value of each keyword in the first keyword set and the matching degree between each keyword and the corresponding category.

In the embodiment shown in fig. 11, after the title information optimization device needs to obtain the first keyword set and the category prediction model of the service object to be optimized, when the title information optimization device needs to determine the target category of the service object to be optimized according to the first keyword set and the category prediction model, the title information optimization device obtains the matching degree between each keyword in the first keyword set and its corresponding category and the category according to the category prediction model, and then obtains the weighted value of each keyword in the first keyword set, optionally obtains the weighted value of each keyword in the first keyword set according to a TF-IDF statistical method, of course, can also obtain the weighted value of each keyword in the first keyword set by other methods, and obtains the matching degree between each keyword and its corresponding category according to the weighted value of each keyword in the first keyword set, and determining the target category, optionally multiplying the weight value by the matching degree, and determining the category with the largest product of the weight value and the matching degree as the target category.

For example, it is assumed that the first keyword set corresponding to the business object to be optimized is: the "spring", "comfort" and "one-piece dress" are shown in table 4, where the weight values and category prediction models corresponding to the keywords are:

TABLE 4

The title information optimization device determines, according to the weight values corresponding to the keywords and the category prediction model shown in table 4, that the product of the weight values corresponding to the categories and the matching degree is as shown in table 5:

TABLE 5

Categories of	Product of weight value and matching degree
		Coat (coat)	0.4*0.9＝0.36
Skirt	0.40.8+0.91＝1.22
		Shoes with air-permeable layer	0.4*0.9＝0.36
Trousers	0.4*0.8＝0.32

The title information optimizing device determines the skirt corresponding to the maximum product (1.22) as the target category according to the product of the weight value and the matching degree corresponding to each category shown in table 5.

It should be noted that table 5 shows the correspondence between the keywords and the categories by way of example only, and does not limit the correspondence between the keywords and the categories.

Based on any of the embodiments in fig. 8 to fig. 11, optionally, the title information optimization apparatus may determine the target business object set in the multiple candidate business object sets through the following feasible implementation manners (S803 in the embodiment shown in fig. 8), specifically, please refer to the embodiment shown in fig. 12.

Fig. 12 is a flowchart of a method for determining a target business object set according to the present invention, please refer to fig. 12, where the method may include:

s1201, judging whether a business object to be optimized has a business object set corresponding to the business object to be optimized;

if yes, go to S1202;

If not, executing S1203-S1204;

s1202, determining a business object set corresponding to a business object to be optimized as a target business object set;

s1203, acquiring attribute information of the service object to be optimized, attribute information of each service object set to be selected, and attribute similarity between the attribute information of the service object to be optimized and the attribute information of each service object set to be selected;

s1204, determining a target business object set in the business object sets to be selected according to the attribute similarity between the attribute information of the optimized business object and the attribute information of each business object set to be selected.

As can be seen from the management architecture diagram of the service objects shown in fig. 3, part of the service objects are already classified into the service object set to which they belong, and part of the service objects are not classified into the service object set to which they belong, so that when a target service object set to which the service object to be optimized belongs needs to be determined, the title information optimization apparatus first determines whether the service object to be optimized has a service object set corresponding thereto:

if the business object to be optimized is classified into the business object set to which the business object to be optimized belongs, the title information optimization device can directly determine the business object set corresponding to the business object to be optimized as the target business object set.

If the attribute information does not exist, the title information optimization device needs to acquire the attribute information of the to-be-optimized service object, the attribute information of each to-be-selected service object set and the attribute similarity between the attribute information of the to-be-optimized service object and the attribute information of each to-be-selected service object set, and determines a target service object set in the to-be-selected service object set according to the attribute similarity between the attribute information of the to-be-optimized service object and the attribute information of each to-be-selected service object set.

Optionally, the attribute information of the service object to be optimized may be represented by a feature vector, and accordingly, the attribute information of the service object to be optimized may be obtained by the following feasible implementation manners: the method comprises the steps of obtaining a first keyword set corresponding to a service object to be optimized and the weight value of each keyword in the first keyword set, obtaining a feature vector of the service object to be optimized according to the weight value of each keyword in the first keyword set, and determining the feature vector of the service object to be optimized as attribute information of the service object to be optimized.

For example, assume that the keywords included in the first keyword set and the weight values of the keywords are as shown in table 6:

TABLE 6

Keyword	Weighted value
		Spring season	0.4
(Comfort)	0.4
		One-piece dress	0.9

The title information optimization apparatus may determine the feature vector of the service object to be optimized as (0.4,0.4,0.9) according to table 6.

Optionally, the attribute information of the candidate service object set may be represented by a feature vector, and accordingly, the attribute information of the candidate service object set may be obtained by the following feasible implementation manner: the method comprises the steps of obtaining a feature vector of each service object in a service object set to be selected, determining a central feature vector of the service object set to be selected according to the feature vector of each service object in the service object set to be selected, determining the central feature vector of the service object set to be selected as attribute information of the service object set to be selected, and optionally, a title information optimization device can align, add and average the feature vectors of each service object to obtain the central feature vector of the service object set to be selected.

For example, assume that the candidate business object set includes 3 business objects, which are respectively denoted as business object 1-business object 3, and assume that the feature vectors of business object 1-business object 3 are shown in table 7:

TABLE 7

Identification of business objects	Feature vector
		Business object 1	(0.5,0.45,0.7)
Business object 2	(0.3,0.5,0.8)
		Business object 3	(0.4,0.3,0.8)

The title information optimization device determines the central feature vector of the selected business object set as

I.e. the central feature vector is (0.4, 0.42, 0.77).

In the above process, when the attribute information of the service object to be optimized is represented by the feature vector of the service object to be optimized and the attribute information of the service object set to be selected is represented by the center feature vector of the service object set to be selected, the attribute similarity between the service object to be optimized and the service object set to be selected may be determined according to the cosine included angle between the feature vector of the service object to be optimized and the center feature vector of the service object set to be selected, specifically, the cosine included angle is inversely proportional to the attribute similarity, and the smaller the cosine included angle, the larger the attribute similarity.

Certainly, when the attribute information of the service object to be optimized is represented by the feature vector of the service object to be optimized and the attribute information of the service object set to be selected is represented by the central feature vector of the service object set to be selected, a target service object set may be determined in a plurality of service object sets to be selected directly according to the cosine included angle between the feature vector of the service object to be optimized and the central feature vector of each service object set to be selected, specifically: the title information optimization device respectively obtains cosine included angles between feature vectors of service objects to be optimized and center feature vectors of each service object set to be selected, determines the service object set to be selected with the cosine included angle smaller than a second preset threshold value as a target service object set, or determines N service object sets to be selected with the smallest cosine included angles as the target service object set, wherein attribute similarity corresponding to the cosine included angles with the included angles being the second preset threshold value is equal to a first preset threshold value.

On the basis of any of the above embodiments, the title information optimization apparatus may periodically execute the above scheme to optimize the title information of the service object, and certainly, in the actual application process, in order to save resources of the title information optimization apparatus, the title information optimization apparatus may optimize only the title information with lower accuracy, and optionally, the title information optimization apparatus may determine the accuracy of the title information of the service object according to the transaction information of the service object, specifically: before the title information optimization device optimizes the title information of the business object, the transaction information of the business object is acquired, and the transaction information is judged to meet at least one of the following conditions: and if the transaction information of the business object meets any one of the conditions, which indicates that the accuracy of the title information of the business object is poor, optimizing the title information of the business object by the technical scheme in the embodiment of the method.

In the process, the title information optimizing device only optimizes the business object information with lower accuracy, so that the workload of the title information optimizing device is reduced, and the working efficiency of the title information optimizing device is improved.

In addition to any of the above embodiments, the title information optimization apparatus may periodically generate the category prediction model, or periodically update and maintain the generated category prediction model, and the following describes in detail the process of generating the category prediction model by using the embodiment shown in fig. 13.

Fig. 13 is a flowchart of a method for generating a category prediction model according to the present invention, referring to fig. 13, the method may include:

s1301, acquiring a plurality of search character strings input by a user within a third preset time length, clicked service objects corresponding to the search character strings and the clicked times of the clicked service objects;

s1302, obtaining keywords corresponding to each search string and categories to which each clicked service object belongs;

s1303, generating a category prediction model according to the plurality of search character strings input within the third preset time length, the clicked service object corresponding to each search character string, the clicked times of each clicked service object, the keywords corresponding to each belonging search character string, and the category to which each clicked service object belongs.

In the embodiment shown in fig. 13, when the title information optimization device needs to generate a category prediction model, the title information optimization device obtains a plurality of search character strings input by a user within a third preset time period, clicked service objects corresponding to the search character strings, and clicked times of the clicked service objects, and then the title information optimization device obtains keywords corresponding to each search character string and a category to which each clicked service object belongs; wherein, the search character string is the search information input by the user when searching the service object, for example, the search character string may be a "spring one-piece dress", etc., after the user inputs the search character string, the data server recommends a plurality of service object information to the user, the service object opened by the user to view the detailed information among the plurality of service object information is the clicked number corresponding to the search character string, for example, after the user inputs the search character string "spring one-piece dress", the data server recommends a service object 1-a service object 100 to the user, if the user views the detailed information of the service object 2 and the service object 3, the service object 2 and the service object 3 are the clicked service objects corresponding to the search character string "spring one-piece dress", the title information optimizing device inputs the search character string of all users and the clicked service object corresponding to the search character string, the number of times each clicked business object is clicked can be obtained.

After the title information optimization device obtains the information, the title information optimization device obtains a first corresponding relationship between the search character strings and the clicked business objects according to the identifications of the clicked business objects corresponding to the search character strings and the clicked times of the clicked business objects, wherein the first corresponding relationship comprises the clicked times of the clicked business objects corresponding to the search character strings.

Illustratively, the first correspondence may be as shown in table 8:

TABLE 8

After the title information optimization device obtains the first corresponding relationship, the title information optimization device obtains a second corresponding relationship between the search character string and the category according to the category to which each clicked service object belongs and the first corresponding relationship, wherein the second corresponding relationship includes the clicked times of the category corresponding to the search character string, and specifically: most of the business objects have the categories to which the business objects belong, after the title information optimization device obtains the first corresponding relationship, the title information optimization device obtains the categories to which the business objects belong in the first corresponding relationship, and obtains the second corresponding relationship according to the categories to which the clicked business objects belong and the first corresponding relationship.

For example, on the basis of table 8, it is assumed that the corresponding category of each business object is shown in table 9:

TABLE 9

The title information optimization apparatus may obtain a second correspondence shown in table 10 according to the correspondence between the clicked service object and the category shown in table 9:

watch 10

After the title information optimization device obtains the second corresponding relationship, the title information optimization device obtains a third corresponding relationship between the keyword and the category according to the keyword corresponding to each search string and the second corresponding relationship, where the third corresponding relationship includes the number of times the category is clicked corresponding to the keyword, and optionally, the title information optimization device may obtain the keyword corresponding to the search string in the manner shown in the embodiment of fig. 10.

Illustratively, on the basis of table 10, it is assumed that the keywords corresponding to the search string are as shown in table 11:

TABLE 11

The title information optimizing apparatus can obtain the third correspondence shown in table 12 from the correspondence shown in table 11 between the search string and the keyword:

TABLE 12

After the title information optimization device obtains the third corresponding relationship, the title information optimization device generates a matching degree of each keyword and the category corresponding to the keyword according to the clicked times of the category corresponding to the keyword, and generates a category prediction model according to the third corresponding relationship and the matching degree of the keyword and the category, wherein the matching degree of the keyword and the category refers to the probability that the business object corresponding to the keyword belongs to the category.

Illustratively, on the basis of table 12, the matching pairs of each keyword and its corresponding category obtained by the title information optimization apparatus are shown in table 13:

watch 13

The title information optimization apparatus determines the obtained category prediction model from table 13 as shown in table 14:

TABLE 14

In the process, the title information optimization device generates a category prediction model according to the actual operation of the user, so that the title information optimization device can obtain the accurate category corresponding to the service object to be optimized according to the category prediction model.

It should be noted that the process of generating the category prediction model by the title information optimization device and the process of optimizing the title information of the business object to be optimized by the title information optimization device are two independent processes. The process of generating the category prediction model may be performed at any time before the header information is optimized, and the present invention does not specifically limit the time at which the header information optimizing apparatus generates the category prediction model.

Based on any of the above embodiments, the title information optimization apparatus may periodically generate the popular vocabulary corresponding to each service object set in the e-commerce platform, or periodically update and maintain the popular vocabulary corresponding to each service object set, and a process of generating the popular vocabulary corresponding to each service object set by the title information optimization apparatus is described in detail through the embodiment shown in fig. 14.

Fig. 14 is a flowchart of a method for generating a hot vocabulary corresponding to a business object set according to the present invention, referring to fig. 14, the method may include:

s1401, dividing all the service objects with the same category to obtain a plurality of service object sets, wherein the attribute similarity of the service objects in each service object set is greater than a third preset threshold value, and the plurality of service object sets comprise a target service object set;

s1402, respectively obtaining second keyword sets of all the business object sets to obtain a plurality of second keyword sets;

s1403, respectively counting the keywords in each second keyword set to obtain the heat value of each keyword in each second keyword set;

and S1404, determining hot words corresponding to the service object sets according to the heat values of the keywords in the second keyword sets.

In the embodiment shown in fig. 14, when the title information optimization device needs to obtain the hot vocabulary corresponding to each service object set, the title information optimization device first divides all service objects under one category to obtain a plurality of service object sets, specifically, the title information optimization device may first obtain a third keyword set corresponding to each service object of the same category and a weight value of each keyword in the third keyword set, obtain a feature vector of each service object according to the weight value of each keyword in each third keyword set, then obtain a cosine angle between the feature vectors of every two service objects, and divide all service objects of the same category according to the cosine angle between the feature vectors of every two service objects to obtain a plurality of service object sets, optionally, divide the cosine angle into a plurality of service object sets within a preset range, the manner of obtaining the feature vector of each service object is the same as the manner of obtaining the feature vector of the service object to be optimized in the embodiment shown in fig. 12, and details are not repeated here.

After the title information optimization device obtains a plurality of service object sets, the title information optimization device obtains a second keyword set corresponding to each service object set to obtain a plurality of second keyword sets, for each second keyword set, the title information optimization device performs TF-IDF statistics on the keywords in the second keyword set to obtain the heat value of each keyword in each second keyword set, and determines the hot vocabulary corresponding to each service object set according to the heat value of each keyword in the second keyword set, wherein the higher the heat value is, the higher the importance of the keyword to the service object set is, the more accurate the characteristics of the service object set can be, optionally, the title information optimization device can determine M (M is a positive integer greater than or equal to 1) keywords with the highest heat values as the hot vocabulary of the service object set, alternatively, the title information optimization apparatus may determine the keywords with the heat value greater than the preset heat threshold as the hot words of the business object set.

In the process, the title information optimization device performs TF-IDF statistics on the keywords in the second keyword set of the business object set to obtain the popular vocabulary of each business object set, which is important to the business object set and can reflect the characteristics of one business object set, so that the accuracy of the popular vocabulary of each business object set is ensured.

It should be noted that the process of acquiring the popular vocabulary of each service object set by the title information optimization device and the process of optimizing the title information of the service object to be optimized by the title information optimization device are two independent processes. The process of obtaining the hot words of each business object set can be executed at any time before the header information is optimized, and the time when the header information optimizing device obtains the hot words of each business object set is not particularly limited.

Next, the title information optimization method will be described in detail with the client as an execution subject.

Fig. 15 is a flowchart of a second method for optimizing header information according to the present invention, please refer to fig. 15, which may include:

s1501, receiving a target hot vocabulary which is sent by a data server and corresponds to a service object to be optimized;

s1502, receiving confirmation title information determined by a user according to the title information of the business object to be optimized and the target popular vocabulary;

and S1503, sending the confirmed title information to the data server so that the data server optimizes the title information of the service object to be optimized according to the confirmed title information.

In the embodiment shown in fig. 5, when the user needs to optimize the header information of the service object to be optimized, the user may input the header information of the service object to be optimized in the client, so that the client sends the header information of the service object to be optimized to the data server. The data server can determine the target hot words according to the hot word set corresponding to the target business object set to which the business object to be optimized belongs and the attribute information of the business object to be optimized, and sends the target hot words to the client.

After the client receives the target hot vocabulary corresponding to the business object to be optimized, which is sent by the data server, the client displays the received target hot vocabulary to the user, so that the user can determine and confirm the title information according to the target hot vocabulary. After the user determines that the confirmed title information is obtained, the user can input the confirmed title information in the client side, and the confirmed title information is sent to the data server by the client side, so that the data server optimizes the title information of the service object to be optimized according to the confirmed title information.

According to the title information optimization method provided by the embodiment of the invention, after the client receives the target hot words corresponding to the to-be-optimized service object and sent by the data server, the client receives the confirmed title information determined by the user according to the title information of the to-be-optimized service object and the target hot words, and sends the confirmed title information to the data server, so that the data server optimizes the title information of the to-be-optimized service object according to the confirmed title information. In the process, the target hot vocabulary is determined by the data server according to the hot vocabulary set corresponding to the target business object set to which the business object to be optimized belongs and the attribute information of the business object to be optimized, so that the target hot vocabulary can accurately reflect the characteristic information of the business object to be optimized, and therefore, the title information of the business object to be optimized can be accurately optimized through the target hot vocabulary, and the accuracy of recommending the business object to the user by the data server is improved.

Based on the embodiment shown in fig. 15, optionally, the client may obtain the confirmation header information determined by the user according to the header information of the business object to be optimized and the target topical vocabulary through a plurality of possible implementation manners (S1502 shown in the embodiment shown in fig. 15), and hereinafter, three possible implementation manners are described through the embodiments shown in fig. 16 to fig. 21.

Fig. 16 is a first flowchart of a method for acquiring confirmation header information according to the present invention, please refer to fig. 16, where the method may include:

s1601, displaying title information and target hot words of the business object to be optimized;

s1602, first confirmation title information input by the user according to the title information and the target popular vocabulary is received.

In the embodiment shown in fig. 16, after the client receives the target hot vocabulary sent by the data server, the client obtains the title information of the business object to be optimized, and displays the title information of the business object to be optimized and the target hot vocabulary.

The user can determine the first confirmed title information according to the displayed title information of the business object to be optimized and the target popular vocabulary. The client may further display a title information input box so that the user may input the first confirmation title information in the title information input box through the input device, so that the client acquires the first confirmation title information input by the user.

Next, the method shown in fig. 16 will be described in detail by specific examples with reference to the schematic diagram of the client interface shown in fig. 17.

Fig. 17 is a schematic diagram of a client interface according to the present invention, which is shown in fig. 17 and includes an

interface

1701 and 1702.

Assuming that a service object to be optimized is a service object 1, the header information of the service object 1 is: skirt long in spring, and then supposing that the data server determines that the target hot vocabulary of the business object 1 is: "2016", "personality", and "Europe and America".

After the data server determines to obtain the target hot vocabulary of the business object 1, the data server sends the target hot vocabulary of the business object 1 to the client. After the client receives the target hit vocabulary of the business object 1, the client displays the title information and the target hit vocabulary of the business object 1, specifically, see interface 1701.

In the interface 1701, including the title information (long spring skirt), the target topical vocabulary ("2016", "personality", "europe and america") of the business object 1, and the optimized title input box M, the user can input the confirmation title information in the optimized title input box M according to the title information and the target topical vocabulary of the business object 1.

In the interface 1702, assuming that the confirmation title information determined by the user according to the title information of the business object 1 and the target popular vocabulary is "2016 spring skirt long-style individual europe and america", the user may input "2016 spring skirt long-style individual europe and america" in the optimization title input box M and click on the "confirm" button, so that the client determines "2016 spring skirt long-style individual europe and america" as the confirmation title information.

In the process, the data server sends the target hot words to the client, and the user determines the optimized title information according to the target hot words at the client, so that the flexibility of optimizing the title information is improved.

Fig. 18 is a flowchart of a second method for acquiring confirmation header information according to the present invention, please refer to fig. 18, where the method may include:

s1801, receiving title information to be confirmed sent by a data server, wherein the title information to be confirmed comprises title information of a business object to be optimized and a target hot vocabulary;

s1802, displaying title information to be confirmed;

s1803, receiving confirmation information which is input by a user and corresponds to the title information to be confirmed;

and S1804, determining the title information to be confirmed as the confirmation title information according to the confirmation information.

In the embodiment shown in fig. 18, the data server adds the target hot vocabulary to the header information of the business object to be optimized, obtains the header information to be confirmed, and sends the header information to be confirmed to the client. After the client receives the title information to be confirmed, the client displays the title information to be confirmed. Optionally, the client may also display the title information of the service object to be optimized.

Optionally, the client may also display a "confirm" button and a "modify" button. If the user approves the title information to be confirmed, the user can click the 'confirmation' button to input confirmation information in the client, and the client determines the title information to be confirmed as the confirmation title information according to the confirmation information input by the user.

Next, the method shown in fig. 18 will be described in detail by specific examples with reference to the schematic diagram of the client interface shown in fig. 19.

Fig. 19 is a schematic diagram of a client interface provided by the present invention, please refer to fig. 19, which includes an interface 1901.

Assuming that a service object to be optimized is a service object 1, the header information of the service object 1 is: the skirt is long in spring, and the data server determines that the target hot vocabulary of the business object 1 is as follows: "2016", "personality", and "Euramerican", the data server determines that the obtained title information to be confirmed is "2016 spring skirt long style personality Euramerican" according to the title information of the business object 1 and the target popular vocabulary.

After the data server determines to obtain the title information to be confirmed of the business object 1, the data server sends the title information to be confirmed to the client. After receiving the title information to be confirmed, the client displays the title information of the business object 1 and the title information to be confirmed, specifically, please refer to the interface 1901.

The interface 1901 includes title information of the business object 1 (spring skirt long style) and title information to be confirmed (2016 spring skirt long style personality europe and america). If the user approves the title information to be confirmed, the user can click the 'confirm' button to input the confirmation information in the client, so that the client determines the title information to be confirmed (2016 spring skirt long style personality Europe and America) as the confirmation title information according to the confirmation information.

Fig. 20 is a flowchart of a third method for acquiring confirmation header information according to the present invention, please refer to fig. 20, which may include:

s2001, receiving to-be-confirmed title information sent by the data server, wherein the to-be-confirmed title information comprises title information of a to-be-optimized business object and a target hot vocabulary;

s2002, displaying the title information to be confirmed;

s2003, receiving modification operation input by a user to the title information to be confirmed, wherein the modification operation is used for modifying the position of a target popular vocabulary in the title information and/or modifying the vocabulary included in the title information to be confirmed;

And S2004, determining second confirmation header information according to the modification operation.

It should be noted that S2001-S2002 is the same as S1801-S1802, and is not described herein again.

After the client displays the title information to be confirmed, the client may also display a "confirm" button and a "modify" button. If the user does not recognize the title information to be confirmed, the user can click the "modify" button to modify the position of the target popular vocabulary in the title information and/or modify the vocabulary included in the title information to be confirmed. And the client determines second confirmation title information according to the modification operation input by the user.

Next, the method shown in fig. 20 is described in detail by specific examples with reference to the schematic diagram of the client interface shown in fig. 21.

Fig. 21 is a schematic diagram of a client interface provided by the present invention, please refer to fig. 21, which includes an

interface

2101 and 2105.

After the data server determines to obtain the title information to be confirmed of the business object 1, the data server sends the title information to be confirmed to the client. After receiving the title information to be confirmed, the client displays the title information of the service object 1 and the title information to be confirmed, specifically, please refer to the interface 2101.

The interface 2101 includes title information of the business object 1 (spring skirt long style) and title information to be confirmed (2016 spring skirt long style personality europe and america). If the user does not recognize the title information to be confirmed, the user may click on the "modify" button and cause the current interface to jump to the interface 2102.

In the interface 2102, the words in the header information to be confirmed (the target popular words and the words in the header information of the service object to be optimized) are displayed, and the delete button P and the add button Q corresponding to each word are displayed. When a user needs to delete a vocabulary in the title information to be confirmed, the user can click a deletion button corresponding to the vocabulary. When a user needs to add a new vocabulary in the title to be confirmed, the user can click the new button, and the client displays the input box so that the user can input the new vocabulary in the input box. Assuming that the user needs to delete the "long" vocabulary in the title information to be confirmed, the user may click on a delete button corresponding to the "long" vocabulary, and cause the current interface to jump to the interface 2103.

In the interface 2103, the "long" vocabulary is deleted from the header information to be confirmed. The user can also drag each vocabulary to modify the position of each vocabulary. Assuming that the user needs to interchange the positions of the two words of "personality" and "europe and america", the user may select the word of "europe and america" and drag the word of "europe and america" to the position before the word of "personality". Of course, the user can also select the "personality" vocabulary and drag the "personality" vocabulary to the position of the "european and american" vocabulary, so that the current interface jumps to the interface 2104.

In the interface 2104, the positions of "europe and america" and "personality" are interchanged. After the user completes modifying the title information to be confirmed, the user may click on the "ok" button to cancel displaying each vocabulary in the interface and cause the current interface to jump to the interface 2105.

In the interface 2105, the confirmation title information "2016 european and american style skirt in spring" is displayed.

In the embodiments shown in fig. 18-fig. 21, the data server first determines the title information to be confirmed according to the target topical vocabulary, and the user determines the optimized title information according to the title information to be confirmed, so as to further improve the flexibility of optimizing the title information.

The method shown in the above embodiment will be described in detail below by taking an interaction process between a data server and a client as an example.

Fig. 22 is a flow chart of a third method for optimizing header information according to the present invention, please refer to fig. 22, which may include:

s2201, a user inputs title information of a business object to be optimized in a client;

s2202, the client sends the title information of the service object to be optimized to the data server;

s2203, the data server determines a target business object set to which a business object to be optimized belongs;

s2204, the data server acquires a hot vocabulary set corresponding to the target business object set and user characteristics corresponding to the business objects to be optimized;

s2205, the data server determines a target popular vocabulary in the popular vocabulary set according to the user characteristics;

s2206, the data server sends target hot words to the client corresponding to the business object to be optimized;

s2207, the client receives confirmation title information determined by the user according to the title information of the business object to be optimized and the target popular vocabulary;

s2208, the client sends confirmation title information to the data server;

s2209, the data server optimizes the title information of the business object to be optimized according to the confirmed title information.

It should be noted that S2201-S2210 have been described in detail in the foregoing embodiments, and are not repeated in the embodiments of the present invention.

In the above process, the data server and the client (user) jointly optimize the header information of the business object to be optimized. The target hot words are determined according to the user characteristics corresponding to the service object to be optimized and the hot word set of the target service object set, so that the target hot words can better reflect the characteristic information of the service object to be optimized, the user can determine and obtain accurate confirmed title information according to the target keywords, and the accuracy of recommending the service object to the user by the data server is improved.

Fig. 23 is a fourth flowchart of a title information optimization method provided by the present invention, please refer to fig. 23, where the method may include:

s2301, determining at least one business object set included in the category;

s2302, acquiring a first popular vocabulary set corresponding to the category and a second popular vocabulary set corresponding to each business object set;

s2303, respectively sending corresponding second hot vocabulary sets to the clients corresponding to the business object sets, so that the user can optimize the title information of the business objects in the business object sets according to the second hot vocabulary sets;

S2304, sending a first hot vocabulary set to a client corresponding to an unclassified business object in the category, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first hot vocabulary set.

It should be noted that the concepts of categories, service object sets, and popular vocabularies shown in the embodiment of the present invention are the same as those shown in the above embodiments of fig. 1 to 22, and are not described herein again.

In the actual application process, the title information optimization device determines at least one service object set included in the category, and acquires a first popular vocabulary set corresponding to the category and a second popular vocabulary set corresponding to each service object set.

After the title information optimization device obtains the second hot vocabulary sets corresponding to the business object sets, the title information optimization device sends the corresponding second hot vocabulary sets to the clients corresponding to the business object sets respectively, so that a user can optimize the title information of the business objects in the business object sets according to the second hot vocabulary sets. Optionally, the title information optimizing apparatus may determine the client corresponding to each service object in the service object set, and send the second popular vocabulary set corresponding to the service object set to the client corresponding to each service object, respectively.

After the title information optimization device obtains a first hot vocabulary set corresponding to the category, the title information optimization device sends the first hot vocabulary set to a client corresponding to an unclassified business object in the category, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first hot vocabulary set. Optionally, the header information optimization device may obtain class classification business objects included in the class, determine clients corresponding to the unclassified business objects, and send the first popular vocabulary sets to the clients corresponding to the unclassified business objects, respectively.

The method shown in the embodiment of fig. 23 will be described in detail below by specific examples.

For example, it is assumed that category 1 includes 3 service object sets and 10 unclassified service objects, where the 3 service object sets are respectively denoted as service object set 1-service object set 3, and the 10 unclassified service objects are respectively denoted as service object 1-service object 10. Assume that the popular vocabulary sets corresponding to the service object sets of category 1 and level are shown in table 15:

watch 15

Business object set 1	Popular vocabulary set 1
		Business object set 2	Popular vocabulary set 2
Business object set 3	Popular vocabulary set 3
		Category 1	Popular vocabulary set 4

After the title information optimization device determines that the hot vocabulary set shown in table 15 is obtained, the title information optimization device sends the hot vocabulary set 1 to the client corresponding to the service object in the service object set 1, sends the hot vocabulary set 2 to the client corresponding to the service object in the service object set 2, sends the hot vocabulary set 3 to the client corresponding to the service object in the service object set 3, and sends the hot vocabulary set 4 to the clients corresponding to the service objects 1-10, so that the client corresponding to the service object optimizes the title information according to the corresponding hot vocabulary set.

In the process, the title information optimization device sends the hot vocabulary sets corresponding to the business object sets to the clients corresponding to the business objects in different business object sets, and sends the hot vocabulary sets corresponding to the categories to the clients corresponding to the unclassified business objects, so that the hot vocabulary sets received by the clients corresponding to the business objects are all the hot vocabulary sets corresponding to the business objects, and the clients corresponding to the business objects can accurately optimize the title information of the business objects according to the hot vocabulary sets corresponding to the business objects.

On the basis of the embodiment shown in fig. 23, optionally, the title information optimizing apparatus may obtain the second popular vocabulary set corresponding to the business object set according to the following feasible implementation manners: and acquiring a keyword set corresponding to the service object set, acquiring the heat value of each keyword in the keyword set, and determining a second popular vocabulary set corresponding to each service object set according to the heat value of each keyword in the keyword set. It should be noted that the process of determining the second popular vocabulary set in the embodiment of the present invention is similar to the process of determining the popular vocabulary corresponding to each service object set in the embodiment of fig. 14, and details are not repeated here.

Correspondingly, the title information optimization device may obtain the first hot keyword set corresponding to the category according to the following feasible implementation manners: and performing de-duplication processing on the hot keywords in each second hot keyword set, and determining a first hot vocabulary set according to each second hot keyword set subjected to de-duplication processing.

Based on the embodiment shown in fig. 23, in order to improve the accuracy of sending the hot vocabulary to each service object, optionally, the title information optimization apparatus may further obtain the user characteristics corresponding to each service object, determine the target hot vocabulary corresponding to each service object in the second hot vocabulary set according to the user characteristics of each service object, and send the corresponding target hot vocabulary to each service object.

Fig. 24 is a fifth flowchart of a title information optimization method provided in the present invention, please refer to fig. 24, where the method may include:

s2401, receiving a popular vocabulary set sent by a data server;

s2402, acquiring title information of a business object corresponding to the popular vocabulary set;

s2403, receiving confirmation title information determined by a user according to the title information of the business object and the popular vocabulary set;

s2404, updating the header information corresponding to the business object into the confirmation header information.

In the method shown in the embodiment of fig. 24, after the client receives the popular vocabulary set sent by the data server, the client obtains the title information of the business object corresponding to the popular vocabulary set, and displays the title information of the business object to be optimized and the popular vocabulary set.

And the user determines the confirmed title information according to the title information of the business object displayed by the client and the popular vocabulary set, and updates the title information corresponding to the business object into the confirmed title information. Optionally, the client may send the confirmation header information and the identifier of the service object to the data server, so that the data server updates the header information of the service object to the confirmation header information.

In the process, the hot vocabulary sets received by the client corresponding to each business object are all the corresponding hot vocabulary sets, so that the client corresponding to each business object can accurately optimize the title information of the client according to the corresponding hot vocabulary sets.

Based on the embodiment shown in fig. 24, optionally, the popular vocabulary set may further include a weight value of each popular vocabulary; accordingly, the client can display the title information of the business object and the hot vocabulary set and the weight values of all hot vocabularies of the hot vocabulary set, so that a user can input confirmation title information according to the title information, the hot vocabulary set and the weight values of all hot vocabularies.

Fig. 25 is a schematic structural diagram of a first title information optimization apparatus provided in the present invention, please refer to fig. 25, which may include:

the first determining module 11 is configured to determine a target business object set to which a business object to be optimized belongs;

a first obtaining module 12, configured to obtain a popular vocabulary set corresponding to the target business object set and user characteristics corresponding to the business object to be optimized;

a second determining module 13, configured to determine a target popular vocabulary in the popular vocabulary set according to the user characteristic;

And the optimization module 14 is configured to optimize the header information of the service object to be optimized according to the target popular vocabulary.

The title information optimization device provided by the embodiment of the invention can execute the technical scheme shown in the method embodiment, and the implementation principle and the beneficial effect are similar, so that the detailed description is omitted.

Fig. 26 is a schematic structural diagram of a second title information optimization apparatus according to the second embodiment of the present invention, and referring to fig. 26, on the basis of the embodiment shown in fig. 25, the second determining module 13 includes a first obtaining unit 13-1 and a first determining unit 13-2, wherein,

the first obtaining unit 13-1 is configured to obtain a matching degree between the user characteristic and each popular keyword in the popular keyword set;

the first determining unit 13-2 is configured to determine a target popular vocabulary in the popular vocabulary set according to a matching degree between the user characteristic and each of the popular keyword sets in the popular keyword set.

In a possible implementation, the first obtaining unit 13-1 is specifically configured to:

In another possible implementation manner, the first obtaining module 13-1 is specifically configured to:

In another possible implementation, the optimization module 14 is specifically configured to:

acquiring at least one current keyword included in the title information;

In another possible implementation, the optimization module 14 is further specifically configured to:

receiving first confirmation header information sent by the client;

In another possible embodiment, the optimization module 14 comprises a second determination unit 14-1 and a sending unit 14-2, wherein,

the second determining unit 14-1 is configured to determine, according to the header information of the to-be-optimized service object and the target popular vocabulary, header information to be confirmed;

the sending unit 14-2 is configured to send the to-be-confirmed title information to the client corresponding to the to-be-optimized service object, so that a user determines the optimized title information according to the to-be-confirmed title information.

In another possible implementation, the second determining unit 14-1 is specifically configured to:

In another possible embodiment, the optimization module further comprises a receiving unit 14-3 and a third determining unit 14-4, wherein,

the sending unit 14-2 is specifically configured to send the to-be-confirmed header information to the client corresponding to the to-be-optimized service object;

the receiving unit 14-3 is configured to receive the acknowledgement information sent by the client;

the third determining unit 14-4 is configured to determine, according to the confirmation information, the header information to be confirmed as the optimized header information of the service object to be optimized.

In another possible implementation manner, the sending unit 14-2 is further configured to send the to-be-confirmed header information to a client corresponding to the to-be-optimized service object;

the receiving unit 14-3 is further configured to receive second confirmation header information sent by the client, where the second confirmation header information is obtained by modifying the title to be confirmed by the user;

The third determining unit 14-4 is further configured to determine the second confirmation header information as the optimized header information of the service object to be optimized.

In another possible embodiment, the first determining module 11 comprises a second obtaining unit 11-1, a fourth determining unit 11-2 and a fifth determining unit 11-3, wherein,

the second obtaining unit 11-1 is configured to obtain a target category to which a service object to be optimized belongs;

the fourth determining unit 11-2 is configured to determine a plurality of service object sets to be selected corresponding to the target category;

the fifth determining unit 11-3 is configured to determine the target business object set in the multiple candidate business object sets.

In another possible implementation manner, the second obtaining unit 11-1 is specifically configured to:

acquiring the weight value of each keyword in the first keyword set;

In another possible implementation manner, the fourth determining unit 11-2 is specifically configured to:

or,

In another possible implementation manner, the second obtaining unit 11-1 and the fourth determining unit 11-2 are specifically configured to:

In another possible embodiment, the apparatus further comprises a second obtaining module 15 and a third determining module 16, wherein,

the second obtaining module 15 is configured to obtain transaction information corresponding to the service object to be optimized before the first determining module 11 determines the target service object set to which the service object to be optimized belongs;

the third determining module 16 is configured to determine that the transaction information corresponding to the to-be-optimized service object meets at least one of the following conditions:

In another possible implementation, the apparatus further includes a third obtaining module 17, a fourth obtaining module 18, and a generating module 19, wherein,

The third obtaining module 17 is configured to, before the second obtaining unit 11-1 determines the target category according to the first keyword set and the category prediction model, obtain a plurality of search strings input by a user within a third preset time period, a clicked service object corresponding to each search string, and a number of times that each clicked service object is clicked;

the fourth obtaining module 18 is configured to obtain a keyword corresponding to each search string and a category to which each clicked service object belongs;

the generating module 19 is configured to generate a category prediction model according to a plurality of search strings input within a third preset time duration, a clicked service object corresponding to each search string, the number of times that each clicked service object is clicked, a keyword corresponding to each belonging search string, and a category to which each clicked service object belongs.

In another possible implementation, the generating module 19 is specifically configured to:

In another possible implementation, the apparatus further includes a dividing module 110, a fifth obtaining module 111, and a fourth determining module 112, wherein,

the dividing module 110 is configured to, before the second obtaining unit 11-1 obtains the popular vocabulary corresponding to the target business object set, divide all business objects belonging to the same category to obtain a plurality of business object sets, where attribute similarity of the business objects in each business object set is greater than a third preset threshold, and the plurality of business object sets include the target business object set;

The fifth obtaining module 111 is configured to obtain a second keyword set of each service object set, obtain a plurality of second keyword sets, and obtain a heat value of each keyword in each second keyword set;

the fourth determining module 112 is configured to determine a popular vocabulary corresponding to each service object set according to the heat value of each keyword in each second keyword set.

In another possible implementation manner, the dividing module 110 is specifically configured to:

Fig. 27 is a schematic structural diagram of another title information optimization apparatus provided in the present invention, please refer to fig. 27, which includes:

the first receiving module 21 is configured to receive a target popular vocabulary corresponding to a service object to be optimized, which is sent by a data server;

the second receiving module 22 is configured to receive confirmation header information determined by the user according to the header information of the to-be-optimized service object and the target popular vocabulary;

the sending module 23 is configured to send the confirmation header information to the data server, so that the data server optimizes the header information of the service object to be optimized according to the confirmation header information.

Fig. 28 is a schematic structural diagram of another title information optimization apparatus according to a second embodiment of the present invention, referring to fig. 28, based on the embodiment shown in fig. 27, the apparatus further includes a display module 24, wherein,

the display module 24 is configured to display the title information of the to-be-optimized service object and the target popular vocabulary;

Correspondingly, the second receiving module 22 is configured to receive first confirmation header information input by the user according to the header information and the target popular vocabulary.

In a possible implementation manner, the first receiving module 21 is specifically configured to:

In another possible embodiment, the display module 24 is further configured to display the title information to be confirmed;

correspondingly, the second receiving module 22 is specifically configured to receive confirmation information corresponding to the to-be-confirmed title information, which is input by a user, and determine the to-be-confirmed title information as the confirmation title information according to the confirmation information.

correspondingly, the second receiving module 22 is specifically configured to receive a modification operation input by the user on the to-be-confirmed header information, where the modification operation is used to modify a position of the target popular vocabulary in the header information and/or modify a vocabulary included in the to-be-confirmed header information, and determine the second confirmed header information according to the modification operation.

In another possible implementation manner, the second receiving module 22 is further configured to receive, before the first receiving module receives the target popular vocabulary sent by the data server, the header information of the business object to be optimized, which is input by the user;

correspondingly, the sending module 23 is further configured to send the header information of the service object to be optimized to the data server, so that the data server determines the target popular vocabulary according to the popular vocabulary set corresponding to the target service object set to which the service object to be optimized belongs and the attribute information of the service object to be optimized.

Fig. 29 is a schematic structural diagram of a first title information optimization apparatus according to another embodiment of the present invention, please refer to fig. 29, which includes:

a determining module 31, configured to determine at least one business object set included in the category;

an obtaining module 32, configured to obtain a first popular vocabulary set corresponding to the category and a second popular vocabulary set corresponding to each service object set;

A sending module 33, configured to send corresponding second popular vocabulary sets to clients corresponding to the service object sets, respectively, so that a user optimizes title information of service objects in the service object sets according to the second popular vocabulary sets;

the sending module 33 is further configured to send the first popular vocabulary set to a client corresponding to an unclassified business object in the category, where the unclassified business object does not belong to any business object set in the category, so that a user optimizes the header information of the unclassified business object according to the first popular vocabulary set.

In a possible implementation, the obtaining module 32 is specifically configured to:

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

In another possible implementation, the obtaining module 32 is specifically configured to: performing deduplication processing on the top keywords in each second top keyword set;

Fig. 30 is a schematic structural diagram of another title information optimization apparatus provided by the present invention, referring to fig. 30, based on the embodiment shown in fig. 29, the sending module 33 includes a determining unit 33-1 and a sending unit 33-2, wherein,

the determining unit 33-1 is configured to determine a client corresponding to each service object in the service object set;

the sending unit 33-2 is configured to send the second popular vocabulary sets corresponding to the business object sets to the clients corresponding to the business objects, respectively.

In another possible implementation manner, the sending unit 33-2 is specifically configured to:

acquiring user characteristics corresponding to each business object;

In another possible implementation manner, the sending module 33 is specifically configured to:

acquiring the class classification business object included in the class;

determining a client corresponding to each unclassified business object;

Fig. 31 is a schematic structural diagram of a header information optimization apparatus according to another embodiment of the present invention, please refer to fig. 31, which includes:

a first receiving module 41, configured to receive a popular vocabulary set sent by a data server;

an obtaining module 42, configured to obtain header information of a business object corresponding to the popular vocabulary set;

a second receiving module 43, configured to receive confirmation header information determined by the user according to the header information of the service object and the popular vocabulary set;

and an updating module 44, configured to update the header information corresponding to the service object to the confirmation header information.

Fig. 32 is a schematic structural diagram of another title information optimization apparatus according to a second embodiment of the present invention, referring to fig. 32, based on the embodiment shown in fig. 31, the apparatus further includes a display module 45, wherein,

the display module 45 is configured to display the title information of the business object and the popular vocabulary set;

correspondingly, the second receiving module 43 is configured to receive confirmation header information input by the user according to the header information and the popular vocabulary set.

In a possible implementation manner, the popular vocabulary set further includes a weight value of each popular vocabulary;

correspondingly, the display module 45 is configured to display the title information of the service object, the popular vocabulary set, and the weight values of the popular vocabularies in the popular vocabulary set;

the second receiving module 43 is configured to receive confirmation header information input by the user according to the header information, the popular vocabulary sets, and the weight values of the popular vocabularies.

In another possible implementation, the updating module 44 is specifically configured to:

Fig. 33 is a schematic structural diagram of a data server according to the first embodiment of the present invention, please refer to fig. 33, where the data server includes a processor 51, a memory 52 for storing application programs, and a communication bus 53 for implementing communication connection between elements, where the processor 51 is configured to read the application programs in the memory 52 and execute the following operations:

The data server provided in the embodiment of the present invention may execute the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.

In a possible implementation, the processor 51 is specifically configured to:

In another possible implementation, the processor 51 is specifically configured to:

In another possible embodiment, the processor 51 is specifically configured to add the target topical vocabulary to the header information of the business object to be optimized.

acquiring at least one current keyword included in the title information;

receiving first confirmation header information sent by the client;

Fig. 34 is a schematic structural diagram of a second data server provided by the present invention, referring to fig. 34 on the basis of the embodiment shown in fig. 33, the data server further includes a communication port 54, wherein the processor 51 is specifically configured to:

and sending the title information to be confirmed to the client corresponding to the service object to be optimized through the communication port 54, so that the user determines the optimized title information according to the title information to be confirmed.

sending the title information to be confirmed to the client corresponding to the service object to be optimized through the communication port 54;

Receiving the confirmation information sent by the client through the communication port 54;

receiving second confirmation header information sent by the client through the communication port 54, where the second confirmation header information is obtained by modifying the title to be confirmed by the user;

acquiring a target category to which a service object to be optimized belongs;

In another possible implementation, the processor 51 is specifically configured to: judging whether the business object to be optimized has a category corresponding to the business object to be optimized;

In another possible implementation, the processor 51 is specifically configured to: according to the category prediction model, acquiring each keyword in the first keyword set, a category corresponding to the keyword and a matching degree of the keyword;

acquiring the weight value of each keyword in the first keyword set;

In another possible implementation, the processor 51 is specifically configured to: judging whether the business object to be optimized has a business object set corresponding to the business object to be optimized;

In another possible implementation, the processor 51 is specifically configured to: determining a to-be-selected business object set with the characteristic similarity larger than the first preset threshold as the target business object set;

or,

In another possible implementation, the processor 51 is specifically configured to: and obtaining a cosine included angle between the feature vector of the service object to be optimized and the central feature vector of the service object set to be selected, and determining the feature similarity according to the cosine included angle.

In another possible implementation, the processor 51 is specifically configured to: respectively acquiring cosine included angles between the feature vectors of the business objects to be optimized and the central feature vectors of all the business object sets to be selected;

In another possible implementation manner, the processor 51 is further configured to, before the processor 51 determines a target business object set to which a business object to be optimized belongs, obtain transaction information corresponding to the business object to be optimized;

In another possible embodiment, the processor 51 is further configured to:

Before the processor 51 determines the target category according to the first keyword set and the category prediction model, acquiring a plurality of search strings input by a user within a third preset time period, clicked service objects corresponding to the search strings, and clicked times of the clicked service objects;

In another possible implementation, the processor 51 is specifically configured to: obtaining a first corresponding relation between the search character strings and the clicked service objects according to the identification of the clicked service objects corresponding to the search character strings and the clicked times of the clicked service objects, wherein the first corresponding relation comprises the clicked times of the clicked service objects corresponding to the search character strings;

In another possible embodiment, the processor 51 is further configured to:

before the processor 51 obtains a hot vocabulary corresponding to a target business object set, dividing all business objects with the same category to obtain a plurality of business object sets, wherein the attribute similarity of the business objects in each business object set is greater than a third preset threshold, and the plurality of business object sets comprise the target business object set;

In another possible implementation, the processor 51 is specifically configured to: acquiring a third keyword set corresponding to each business object with the same category and the weight value of each keyword in the third keyword set;

Fig. 35 is a schematic structural diagram of a client according to the first embodiment of the present invention, which includes a processor 61, a communication port 62, an input device 63, a memory 64 for storing an application program, and a communication bus 65 for implementing communication connection between elements, wherein,

The processor 61 is configured to receive, through the communication port 62, a target hot vocabulary corresponding to a service object to be optimized, which is sent by the data server;

the input device 63 is configured to receive confirmation header information determined by a user according to the header information of the to-be-optimized service object and the target popular vocabulary;

the processor 61 is further configured to send the confirmation header information to the data server through the communication port, so that the data server optimizes the header information of the to-be-optimized service object according to the confirmation header information.

The client provided by the embodiment of the present invention may execute the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects thereof are similar, and are not described herein again.

Fig. 36 is a schematic structural diagram of a second client according to the present invention, referring to fig. 36 on the basis of the embodiment shown in fig. 35, the client further includes a display device 66, wherein,

the display device 66 is configured to display the title information of the to-be-optimized business object and the target popular vocabulary;

correspondingly, the input device 63 is specifically configured to receive first confirmation header information input by the user according to the header information and the target popular vocabulary.

In a possible implementation manner, the processor 61 is specifically configured to receive, through the communication port, to-be-confirmed header information sent by the data server, where the to-be-confirmed header information includes header information of the to-be-optimized business object and the target hit vocabulary.

In another possible embodiment, the display device 66 is further configured to display the title information to be confirmed;

correspondingly, the input device 63 is specifically configured to receive confirmation information corresponding to the header information to be confirmed, which is input by a user;

the processor 61 is specifically configured to determine, according to the confirmation information, the header information to be confirmed as the confirmation header information.

correspondingly, the input device 63 is specifically configured to receive a modification operation input by the user on the header information to be confirmed, where the modification operation is used to modify a position of the target popular vocabulary in the header information and/or modify a vocabulary included in the header information to be confirmed;

the processor 61 is specifically configured to determine second confirmation header information according to the modification operation.

In another possible embodiment, the processor 61 is further configured to receive, through the communication port, header information of the business object to be optimized, which is input by a user, before the processor receives, through the communication port, the target popular vocabulary sent by the data server;

correspondingly, the processor 61 is specifically configured to send header information of the service object to be optimized to a data server through the communication port, so that the data server determines a target hot vocabulary according to a hot vocabulary set corresponding to a target service object set to which the service object to be optimized belongs and attribute information of the service object to be optimized.

Fig. 37 is a schematic structural diagram of another data server provided by the present invention, please refer to fig. 37 including a processor 71, a communication port 72, a memory 73 for storing an application program, and a communication bus 74 for implementing communication connection between elements, where the processor 71 is configured to read the application program in the memory 73 and perform the following operations:

Determining at least one business object set included in the category;

respectively sending corresponding second hot vocabulary sets to the clients corresponding to the business object sets through the communication ports 72, so that a user can optimize the title information of the business objects in the business object sets according to the second hot vocabulary sets;

and sending the first popular vocabulary set to a client corresponding to the unclassified business object in the category through the communication port 72, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first popular vocabulary set.

In a possible implementation, the processor 71 is specifically configured to:

acquiring a keyword set corresponding to the business object set;

Acquiring a heat value of each keyword in the keyword set;

In another possible implementation, the processor 71 is specifically configured to:

acquiring user characteristics corresponding to each business object;

acquiring the class classification business object included in the class;

determining a client corresponding to each unclassified business object;

Fig. 38 is a schematic structural diagram of another client according to the first embodiment of the present invention, please refer to fig. 38, which includes a processor 81, a communication port 82, an input device 83, a memory 84 for storing an application program, and a communication bus 85 for implementing communication connection between elements, wherein,

the processor 81 is configured to receive a popular vocabulary set sent by a data server through the communication port 82;

the processor 81 is further configured to obtain header information of a business object corresponding to the popular vocabulary set;

the input device 83 is configured to receive confirmation header information determined by a user according to the header information of the business object and the popular vocabulary set;

The processor 81 is further configured to update the header information corresponding to the service object to the confirmation header information.

Fig. 39 is a schematic structural diagram of another client according to the second embodiment of the present invention, referring to fig. 39, based on the embodiment shown in fig. 38, the client further includes a display device 86, wherein,

the display device 86 is configured to display the title information of the business object and the popular vocabulary set;

correspondingly, the input device 83 is specifically configured to receive confirmation header information input by the user according to the header information and the popular vocabulary set.

correspondingly, the display device 86 is configured to display the title information of the service object, the popular vocabulary set, and the weight values of the popular vocabularies in the popular vocabulary set;

the input device 83 is specifically configured to receive confirmation header information input by the user according to the header information, the popular vocabulary sets, and the weight values of the popular vocabularies.

In another possible implementation, the processor 81 is specifically configured to:

Fig. 40 is a schematic structural diagram of a title information optimization system according to the present invention, please refer to fig. 40, which includes a data server 901 and a client 902, wherein,

the data server 901 is configured to determine a target service object set to which a service object to be optimized belongs, obtain a popular vocabulary set corresponding to the target service object set and user characteristics corresponding to the service object to be optimized, determine a target popular vocabulary in the popular vocabulary set according to the user characteristics, and send the target popular vocabulary to a client;

the client 902 is configured to receive a target hot vocabulary corresponding to a service object to be optimized, which is sent by the data server, receive confirmation header information determined by a user according to the header information of the service object to be optimized and the target hot vocabulary, and send the confirmation header information to the data server, so that the data server optimizes the header information of the service object to be optimized according to the confirmation header information.

The title information optimization system provided by the embodiment of the invention can execute the technical scheme shown in the method embodiment, and the implementation principle and the beneficial effect are similar, and are not described again here.

Fig. 41 is a schematic structural diagram of another title information optimization system provided by the present invention, please refer to fig. 41, which includes a data server 1001 and a client 1002, wherein,

the data server 1001 is configured to determine at least one service object set included in a category, obtain a first hot vocabulary set corresponding to the category and a second hot vocabulary set corresponding to each service object set, send the corresponding second hot vocabulary sets to clients corresponding to each service object set, and send the first hot vocabulary sets to clients corresponding to unclassified service objects in the category;

the client 1002 is configured to receive the popular vocabulary set sent by the data server, obtain header information of a service object corresponding to the popular vocabulary set, receive confirmation header information determined by a user according to the header information of the service object and the popular vocabulary set, and update the header information corresponding to the service object to the confirmation header information.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A title information optimization method, comprising:

determining a target business object set to which a business object to be optimized belongs; the target business object set can be one business object set or a plurality of business object sets;

optimizing the title information of the business object to be optimized according to the target popular vocabulary;

the determining a target popular vocabulary in the popular vocabulary set according to the user characteristics comprises:

acquiring the matching degree of the user characteristics and each popular keyword in the popular vocabulary set;

and determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword in the popular vocabulary set.

2. The method of claim 1, wherein the obtaining the degree of matching between the user characteristic and each popular keyword in the popular vocabulary set comprises:

and determining the matching degree of the user characteristics and each popular keyword according to a preset vocabulary category matching table, the first vocabulary category and each second vocabulary category, wherein the preset vocabulary category matching table comprises the matching degree between each two vocabulary categories.

3. The method according to claim 1, wherein the obtaining of the user characteristic corresponding to the service object to be optimized includes:

4. The method according to claim 1, wherein the optimizing the header information of the business object to be optimized according to the target popular vocabulary comprises:

5. The method of claim 4, wherein the adding the target topical vocabulary to the header information of the business object to be optimized comprises:

acquiring at least one current keyword included in the title information;

6. The method according to claim 1, wherein the optimizing the header information of the business object to be optimized according to the target popular vocabulary comprises:

receiving first confirmation header information sent by the client;

7. The method according to claim 1, wherein the optimizing the header information of the business object to be optimized according to the target popular vocabulary comprises:

8. The method according to claim 7, wherein the determining the title information to be confirmed according to the title information of the business object to be optimized and the target popular vocabulary comprises:

9. The method according to claim 7, wherein the sending the to-be-confirmed header information to the client corresponding to the to-be-optimized service object, so that a user determines the optimized header information according to the to-be-confirmed header information, comprises:

receiving confirmation information sent by the client;

10. The method according to claim 7, wherein the sending the to-be-confirmed header information to the client corresponding to the to-be-optimized service object, so that a user determines the optimized header information according to the to-be-confirmed header information, comprises:

11. The method according to claim 1, wherein the determining a target business object set to which the business object to be optimized belongs comprises:

acquiring a target category to which a service object to be optimized belongs;

12. The method according to claim 11, wherein the obtaining of the target category to which the service object to be optimized belongs comprises:

13. The method of claim 12, wherein determining the target category according to the first set of keywords and a category prediction model comprises:

acquiring the weight value of each keyword in the first keyword set;

14. The method of claim 11, wherein the determining the target set of business objects among the plurality of sets of business objects to be selected comprises:

15. The method according to claim 14, wherein the determining a target business object set in the candidate business object set according to the feature similarity between the feature information of the optimized business object and the feature information of each candidate business object set comprises:

determining a to-be-selected business object set with the characteristic similarity larger than a first preset threshold as the target business object set;

or,

16. The method of claim 14,

the acquiring of the feature information of the service object to be optimized includes:

17. The method according to claim 16, wherein the obtaining of the feature similarity between the feature information of the service object to be optimized and the feature information of the service object set to be selected comprises:

18. The method of claim 16, wherein determining a target business object set in the candidate business object sets according to feature similarity between feature information of the optimized business object and feature information of each candidate business object set comprises:

and determining a set of service objects to be selected with cosine included angles smaller than a second preset threshold as the target service object set, or determining N sets of service objects to be selected with the smallest cosine included angles as the target service object set, wherein the feature similarity corresponding to the cosine included angles with the included angles being the second preset threshold is equal to the first preset threshold.

19. The method according to claim 12 or 16, wherein the obtaining of the first keyword set corresponding to the service object to be optimized includes:

20. The method according to any of claims 12-17, wherein before determining the target business object set to which the business object to be optimized belongs, further comprising:

21. The method of claim 12, further comprising, prior to said determining the target category according to the first set of keywords and a category prediction model:

22. The method of claim 21, wherein generating a category prediction model according to a plurality of search strings, clicked service objects corresponding to the search strings, clicked times of the clicked service objects, keywords corresponding to the search strings, and categories to which the clicked service objects belong, which are input within a third preset time period, comprises:

23. The method according to any one of claims 12-17, wherein before obtaining the popular vocabulary corresponding to the target business object set, further comprising:

acquiring a heat value of each keyword in each second keyword set;

24. The method according to claim 23, wherein said dividing all the service objects of the same category into a plurality of service object sets comprises:

25. A title information optimization method, comprising:

determining at least one business object set included in the category;

sending the first popular vocabulary set to a client corresponding to an unclassified business object in the category, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first popular vocabulary set;

acquiring a second popular vocabulary set corresponding to the business object set, wherein the second popular vocabulary set comprises the following steps:

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

26. The method of claim 25, wherein obtaining a first set of topical words corresponding to a category comprises:

performing de-duplication processing on the hot keywords in each second hot vocabulary set;

And determining the first popular vocabulary set according to each second popular vocabulary set after the de-duplication processing.

27. The method of claim 25, wherein sending the corresponding second set of topical words to the respective clients corresponding to the respective sets of business objects comprises:

28. The method of claim 27, wherein sending the second popular vocabulary set corresponding to the business object set to the client corresponding to each business object respectively comprises:

acquiring user characteristics corresponding to each business object;

29. The method of any of claims 25-28, wherein sending the first popular vocabulary set to a client corresponding to an unclassified business object in the category comprises:

Acquiring the unclassified business object included in the category;

determining a client corresponding to each unclassified business object;

30. A title information optimization apparatus, comprising:

the first determining module is used for determining a target business object set to which a business object to be optimized belongs; the target business object set can be one business object set or a plurality of business object sets;

the optimization module is used for optimizing the title information of the business object to be optimized according to the target popular vocabulary;

the second determination module includes a first acquisition unit and a first determination unit, wherein,

the first obtaining unit is used for obtaining the matching degree of the user characteristics and each popular keyword in the popular vocabulary set;

The first determining unit is used for determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword in the popular vocabulary set.

31. The apparatus of claim 30, wherein the optimization module is specifically configured to:

acquiring at least one current keyword included in the title information;

32. The apparatus of claim 30, wherein the optimization module is specifically configured to:

receiving first confirmation header information sent by the client;

33. The apparatus according to any of claims 30-32, wherein the first determining means comprises a second obtaining unit, a fourth determining unit, and a fifth determining unit, wherein,

34. The apparatus according to claim 33, wherein the second obtaining unit is specifically configured to:

35. The apparatus according to claim 33, wherein the fourth determining unit is specifically configured to:

36. The apparatus according to claim 33, wherein the fourth determining unit is specifically configured to:

37. The apparatus according to any of claims 30-32, further comprising a second obtaining module and a third determining module, wherein,

38. The apparatus of claim 33, further comprising a third acquisition module, a fourth acquisition module, and a generation module, wherein,

The third obtaining module is configured to, before the second obtaining unit determines the target category according to the first keyword set and the category prediction model, obtain a plurality of search strings input by the user within a third preset time period, a clicked service object corresponding to each search string, and the clicked times of each clicked service object;

39. The apparatus of claim 33, further comprising a partitioning module, a fifth obtaining module, and a fourth determining module, wherein,

40. A title information optimization apparatus, comprising:

the sending module is further configured to send the first popular vocabulary set to a client corresponding to an unclassified business object in the category, where the unclassified business object does not belong to any business object set in the category, so that a user optimizes title information of the unclassified business object according to the first popular vocabulary set;

The acquisition module is specifically configured to:

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

41. The apparatus of claim 40, wherein the obtaining module is specifically configured to: performing de-duplication processing on the hot keywords in each second hot vocabulary set;

42. A data server comprising a processor and a memory for storing an application program, the processor being configured to read the application program from the memory and perform the following operations:

and determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword set in the popular vocabulary set.

43. A data server comprising a processor, a communication port, and a memory for storing an application program, the processor being configured to read the application program from the memory and perform the following operations:

determining at least one business object set included in the category;

sending the first popular vocabulary set to a client corresponding to an unclassified business object in the category through the communication port, wherein the unclassified business object does not belong to any business object set in the category, so that a user can optimize the title information of the unclassified business object according to the first popular vocabulary set;

acquiring a keyword set corresponding to the business object set;

acquiring a heat value of each keyword in the keyword set;

44. A title information optimization system comprises a data server and a client, wherein,

the data server is used for determining a target business object set to which a business object to be optimized belongs, acquiring a hot vocabulary set corresponding to the target business object set and user characteristics corresponding to the business object to be optimized, determining a target hot vocabulary in the hot vocabulary set according to the user characteristics, and sending the target hot vocabulary to a client; the determining a target popular vocabulary in the popular vocabulary set according to the user characteristics comprises: acquiring the matching degree of the user characteristics and each popular keyword in the popular vocabulary set; determining a target popular vocabulary in the popular vocabulary set according to the matching degree of the user characteristics and each popular keyword set in the popular vocabulary set;

45. A title information optimization system comprises a data server and a client, wherein,

the data server is used for determining at least one service object set included in a category, acquiring a first hot vocabulary set corresponding to the category and a second hot vocabulary set corresponding to each service object set, respectively sending the corresponding second hot vocabulary sets to clients corresponding to each service object set, so that a user can optimize the title information of service objects in the service object sets according to the second hot vocabulary sets, and sending the first hot vocabulary sets to the clients corresponding to unclassified service objects in the category, wherein the unclassified service objects do not belong to any service object set in the category, so that the user can optimize the title information of the unclassified service objects according to the first hot vocabulary sets; acquiring a second popular vocabulary set corresponding to the business object set, wherein the second popular vocabulary set comprises the following steps: acquiring a keyword set corresponding to the business object set; acquiring a heat value of each keyword in the keyword set; determining a second popular vocabulary set corresponding to each business object set according to the heat value of each keyword in the keyword set;