poster

Diversifying query suggestions based on query documents

Authors:

W. Bruce CroftAuthors Info & Claims

SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval

Pages 891 - 894

https://doi.org/10.1145/2600428.2609467

Published: 03 July 2014 Publication History

Abstract

Many domain-specific search tasks are initiated by document-length queries, e.g., patent invalidity search aims to find prior art related to a new (query) patent. We call this type of search Query Document Search. In this type of search, the initial query document is typically long and contains diverse aspects (or sub-topics). Users tend to issue many queries based on the initial document to retrieve relevant documents. To help users in this situation, we propose a method to suggest diverse queries that can cover multiple aspects of the query document. We first identify multiple query aspects and then provide diverse query suggestions that are effective for retrieving relevant documents as well being related to more query aspects. In the experiments, we demonstrate that our approach is effective in comparison to previous query suggestion methods.

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Cited By

Wang SScells HMourad AZuccon G(2022)Seed-Driven Document Ranking for Systematic Reviews: A Reproducibility StudyAdvances in Information Retrieval10.1007/978-3-030-99736-6_46(686-700)Online publication date: 5-Apr-2022
https://doi.org/10.1007/978-3-030-99736-6_46
Vuong TAndolina SJacucci GRuotsalo T(2021)Does More Context Help? Effects of Context Window and Application Source on Retrieval PerformanceACM Transactions on Information Systems10.1145/347405540:2(1-40)Online publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1145/3474055
Liao ZTajima K(2019)Disjunctive Sets of Phrase Queries for Diverse Query SuggestionIEEE/WIC/ACM International Conference on Web Intelligence10.1145/3350546.3352566(449-455)Online publication date: 14-Oct-2019
https://dl.acm.org/doi/10.1145/3350546.3352566
Show More Cited By

Index Terms

Diversifying query suggestions based on query documents
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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Information & Contributors

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Published In

cover image ACM Conferences

SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval

July 2014

1330 pages

ISBN:9781450322577

DOI:10.1145/2600428

General Chairs:
Shlomo Geva
Queensland University of Technology
,
Andrew Trotman
University of Dunedin
,
Program Chairs:
Peter Bruza
Queensland University of Technology
,
Charles L.A. Clarke
University of Waterloo
,
Kal Järvelin
University of Tampere

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 July 2014

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SIGIR '14

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SIGIR

SIGIR '14: The 37th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 6 - 11, 2014

Queensland, Gold Coast, Australia

Acceptance Rates

SIGIR '14 Paper Acceptance Rate 82 of 387 submissions, 21%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Wang SScells HMourad AZuccon G(2022)Seed-Driven Document Ranking for Systematic Reviews: A Reproducibility StudyAdvances in Information Retrieval10.1007/978-3-030-99736-6_46(686-700)Online publication date: 5-Apr-2022
https://doi.org/10.1007/978-3-030-99736-6_46
Vuong TAndolina SJacucci GRuotsalo T(2021)Does More Context Help? Effects of Context Window and Application Source on Retrieval PerformanceACM Transactions on Information Systems10.1145/347405540:2(1-40)Online publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1145/3474055
Liao ZTajima K(2019)Disjunctive Sets of Phrase Queries for Diverse Query SuggestionIEEE/WIC/ACM International Conference on Web Intelligence10.1145/3350546.3352566(449-455)Online publication date: 14-Oct-2019
https://dl.acm.org/doi/10.1145/3350546.3352566
Wang FQian TLiu BPeng Z(2019)Patent expanded retrieval via word embedding under composite-domain perspectivesFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-018-7056-613:5(1048-1061)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s11704-018-7056-6
Lee GSun ACollins-Thompson KMei QDavison BLiu YYilmaz E(2018)Seed-driven Document Ranking for Systematic Reviews in Evidence-Based MedicineThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3209994(455-464)Online publication date: 27-Jun-2018
https://dl.acm.org/doi/10.1145/3209978.3209994
Shajalal MAono MAzim M(2018)Aspect-based Query Expansion for Search Results Diversification2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR)10.1109/ICIEV.2018.8641004(147-152)Online publication date: Jul-2018
https://doi.org/10.1109/ICIEV.2018.8641004
Hamasaki MGoto MMorgan L(2017)QueryShareProceedings of the 13th International Symposium on Open Collaboration10.1145/3125433.3125463(1-9)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3125433.3125463
Noce LGallo IZamberletti ACalefati A(2017)A Query and Product Suggestion Method for Price Comparison Search EnginesWeb Information Systems and Technologies10.1007/978-3-319-66468-2_1(1-14)Online publication date: 8-Sep-2017
https://doi.org/10.1007/978-3-319-66468-2_1
Korobkin DFomenkov SKravets AKolesnikov S(2017)Methods of Statistical and Semantic Patent AnalysisCreativity in Intelligent Technologies and Data Science10.1007/978-3-319-65551-2_4(48-61)Online publication date: 17-Aug-2017
https://doi.org/10.1007/978-3-319-65551-2_4
Hao XCheng JVosecky JNg W(2017)Towards a Query-Less News Search Framework on TwitterDatabase Systems for Advanced Applications10.1007/978-3-319-55699-4_9(137-152)Online publication date: 22-Mar-2017
https://doi.org/10.1007/978-3-319-55699-4_9
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