poster

A collaborative filtering approach to ad recommendation using the query-ad click graph

Authors:

Tasos Anastasakos,

Dustin Hillard,

Sanjay Kshetramade,

Hema RaghavanAuthors Info & Claims

CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management

Pages 1927 - 1930

https://doi.org/10.1145/1645953.1646267

Published: 02 November 2009 Publication History

Abstract

Search engine logs contain a large amount of click-through data that can be leveraged as soft indicators of relevance. In this paper we address the sponsored search retrieval problem which is to find and rank relevant ads to a search query. We propose a new technique to determine the relevance of an ad document for a search query using click-through data. The method builds on a collaborative filtering approach to discover new ads related to a query using a click graph. It is implemented on a graph with several million edges and scales to larger sizes easily. The proposed method is compared to three different baselines that are state-of-the-art for a commercial search engine. Evaluations on editorial data indicate that the model discovers many new ads not retrieved by the baseline methods. The ads from the new approach are on average of better quality than the baselines.

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Cited By

Liu HLuo S(2024)BIRD: Efficient Approximation of Bidirectional Hidden Personalized PageRankProceedings of the VLDB Endowment10.14778/3665844.366585517:9(2255-2268)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.14778/3665844.3665855
Sharma RSrivastava SAmaran S(2023)Filtering Ads based on User Browsing Data using Data Analytics and Machine Learning2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)10.1109/ICESC57686.2023.10192994(1545-1549)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICESC57686.2023.10192994
Viktoratos ITsadiras A(2021)Personalized Advertising Computational Techniques: A Systematic Literature Review, Findings, and a Design FrameworkInformation10.3390/info1211048012:11(480)Online publication date: 19-Nov-2021
https://doi.org/10.3390/info12110480
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Index Terms

A collaborative filtering approach to ad recommendation using the query-ad click graph
1. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

cover image ACM Conferences

CIKM '09: Proceedings of the 18th ACM conference on Information and knowledge management

November 2009

2162 pages

ISBN:9781605585123

DOI:10.1145/1645953

General Chairs:
David Cheung
University of Hong Kong, Hong Kong
,
Il-Yeol Song
Drexel University, USA
,
Program Chairs:
Wesley Chu
UCLA, USA
,
Xiaohua Hu
Drexel University, USA
,
Jimmy Lin
University of Maryland, USA

Copyright © 2009 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]

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Publication History

Published: 02 November 2009

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CIKM '09

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CIKM '09: Conference on Information and Knowledge Management

November 2 - 6, 2009

Hong Kong, China

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Liu HLuo S(2024)BIRD: Efficient Approximation of Bidirectional Hidden Personalized PageRankProceedings of the VLDB Endowment10.14778/3665844.366585517:9(2255-2268)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.14778/3665844.3665855
Sharma RSrivastava SAmaran S(2023)Filtering Ads based on User Browsing Data using Data Analytics and Machine Learning2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)10.1109/ICESC57686.2023.10192994(1545-1549)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICESC57686.2023.10192994
Viktoratos ITsadiras A(2021)Personalized Advertising Computational Techniques: A Systematic Literature Review, Findings, and a Design FrameworkInformation10.3390/info1211048012:11(480)Online publication date: 19-Nov-2021
https://doi.org/10.3390/info12110480
Xiao LMao HWang S(2020)Research on Mobile Marketing Recommendation Method Incorporating Layout Aesthetic Preference for Sustainable m-CommerceSustainability10.3390/su1206249612:6(2496)Online publication date: 23-Mar-2020
https://doi.org/10.3390/su12062496
Yang XSun DZhu RDeng TGuo ZDing ZQin SZhu YTeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)AiAdsProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330782(1881-1890)Online publication date: 25-Jul-2019
https://dl.acm.org/doi/10.1145/3292500.3330782
Maniadis IVavliakis KSymeonidis A(2019)Banner Personalization for e-CommerceArtificial Intelligence Applications and Innovations10.1007/978-3-030-19823-7_53(635-646)Online publication date: 12-May-2019
https://doi.org/10.1007/978-3-030-19823-7_53
Kong DWu FTang SZhuang YHanjalic ASnoek CWorring MBulterman DHuet BKelliher AKompatsiaris YLi J(2016)Ad Recommendation for Sponsored Search Engine via Composite Long-Short Term MemoryProceedings of the 24th ACM international conference on Multimedia10.1145/2964284.2967254(416-420)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1145/2964284.2967254
Diapouli MPetridis MEvans RKapetanakis S(2016)An Industrial Application of Data Mining Techniques to Enhance the Effectiveness of On-Line AdvertisingResearch and Development in Intelligent Systems XXXIII10.1007/978-3-319-47175-4_30(391-397)Online publication date: 5-Nov-2016
https://doi.org/10.1007/978-3-319-47175-4_30
Lin TNing X(2015)Multi-Perspective Modeling for Click Event PredictionProceedings of the 2015 International ACM Recommender Systems Challenge10.1145/2813448.2813520(1-4)Online publication date: 16-Sep-2015
https://dl.acm.org/doi/10.1145/2813448.2813520
Dave KVarma V(2014)Computational AdvertisingFoundations and Trends in Information Retrieval10.1561/15000000458:4–5(263-418)Online publication date: 29-Oct-2014
https://dl.acm.org/doi/10.1561/1500000045
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