poster

HLBPR: A Hybrid Local Bayesian Personal Ranking Method

Authors:

Xu Chen,

Pengfei Wang,

Zheng Qin,

Yongfeng ZhangAuthors Info & Claims

WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide Web

Pages 21 - 22

https://doi.org/10.1145/2872518.2889349

Published: 11 April 2016 Publication History

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Abstract

Bayesian Personal Ranking(BPR) method is a well-known model due to its high performance in the task of item recommendation. However, this method fail to distinguish user preference among the non-interacted items. In this paper, to enhance traditional BPR's performance, we introduce and analyse a hybrid method, namely Hybrid Local Bayesian Personal Ranking method(HLBPR for short). Our main idea is to construct additional item preference pairs among the products which haven't been purchased, and then utilize the extened pairs to optimize the ranking object. Experiments on two real-world transaction datasets demonstrated the effectiveness of our approach as compared with the state-of-the-art methods.

References

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S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme. Bpr: Bayesian personalized ranking from implicit feedback. In UAI, 2009.

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G.-E. Yap, X.-L. Li, and S. Y. Philip. Effective next-items recommendation via personalized sequential pattern mining. In Database Systems for Advanced Applications, 2012.

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T. Zhao, J. McAuley, and I. King. Leveraging social connections to improve personalized ranking for collaborative filtering. In CIKM, 2014.

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Cited By

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Wu ZMa YCao JPaul ALi X(2023)Multiple feedback based adversarial collaborative filtering with aestheticsInternational Journal of Multimedia Information Retrieval10.1007/s13735-023-00273-w12:1Online publication date: 29-Apr-2023
https://doi.org/10.1007/s13735-023-00273-w
Wang ZYe WChen XZhang WWang ZZou LLiu W(2022)Generative Session-based RecommendationProceedings of the ACM Web Conference 202210.1145/3485447.3512095(2227-2235)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3485447.3512095
Zhang QRen F(2021)Double bayesian pairwise learning for one-class collaborative filteringKnowledge-Based Systems10.1016/j.knosys.2021.107339(107339)Online publication date: Jul-2021
https://doi.org/10.1016/j.knosys.2021.107339
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Index Terms

HLBPR: A Hybrid Local Bayesian Personal Ranking Method
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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Information

Published In

WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide Web

April 2016

1094 pages

ISBN:9781450341448

General Chairs:
Jacqueline Bourdeau
Tele-university (TELUQ), Montreal, QC, Canada
,
Jim A. Hendler
Rensselaer Polytechnic Institute, Troy, NY, USA
,
Roger Nkambou Nkambou
Université du Québec à Montréal, Montreal, QC, Canada
,
Program Chairs:
Ian Horrocks
University of Oxford, UK
,
Ben Y. Zhao
University of California at Santa Barbara, CA, USA

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

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Published: 11 April 2016

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WWW '16

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IW3C2

WWW '16: 25th International World Wide Web Conference

April 11 - 15, 2016

Québec, Montréal, Canada

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WWW '16 Companion Paper Acceptance Rate 115 of 727 submissions, 16%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Wu ZMa YCao JPaul ALi X(2023)Multiple feedback based adversarial collaborative filtering with aestheticsInternational Journal of Multimedia Information Retrieval10.1007/s13735-023-00273-w12:1Online publication date: 29-Apr-2023
https://doi.org/10.1007/s13735-023-00273-w
Wang ZYe WChen XZhang WWang ZZou LLiu W(2022)Generative Session-based RecommendationProceedings of the ACM Web Conference 202210.1145/3485447.3512095(2227-2235)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3485447.3512095
Zhang QRen F(2021)Double bayesian pairwise learning for one-class collaborative filteringKnowledge-Based Systems10.1016/j.knosys.2021.107339(107339)Online publication date: Jul-2021
https://doi.org/10.1016/j.knosys.2021.107339
Yu WHe XPei JChen XXiong LLiu JQin Z(2021)Visually aware recommendation with aesthetic featuresThe VLDB Journal10.1007/s00778-021-00651-yOnline publication date: 27-Feb-2021
https://doi.org/10.1007/s00778-021-00651-y
Wang JHan P(2020)Adversarial Training-based Mean Bayesian Personalized Ranking for Recommender SystemIEEE Access10.1109/ACCESS.2019.2963316(1-1)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2019.2963316
Yang XWang B(2020)Local ranking and global fusion for personalized recommendationApplied Soft Computing10.1016/j.asoc.2020.10663696:COnline publication date: 1-Nov-2020
https://dl.acm.org/doi/10.1016/j.asoc.2020.106636
Li MWang L(2019)A Survey on Personalized News Recommendation TechnologyIEEE Access10.1109/ACCESS.2019.29449277(145861-145879)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2944927
Yu RZhang YYe YWu LWang CLiu QChen ECuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)Multiple Pairwise Ranking with Implicit FeedbackProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3269283(1727-1730)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3269283
Yu WZhang HHe XChen XXiong LQin ZChampin PGandon FMédini LLalmas MIpeirotis P(2018)Aesthetic-based Clothing RecommendationProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186146(649-658)Online publication date: 10-Apr-2018
https://dl.acm.org/doi/10.1145/3178876.3186146
Chen XZhang YAi QXu HYan JQin ZKando NSakai TJoho HLi Hde Vries AWhite R(2017)Personalized Key Frame RecommendationProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3080776(315-324)Online publication date: 7-Aug-2017
https://dl.acm.org/doi/10.1145/3077136.3080776
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Coauthorship networks and academic literature recommendation

A novel user-based collaborative filtering method by inferring tag ratings

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