GBPR: Group preference based Bayesian personalized ranking for one-class collaborative filtering: Group preference based bayesian personalized ranking for one-class collaborative filtering

Weike Pan, Li CHEN

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

163 Citations (Scopus)

Abstract

One-class collaborative filtering or collaborative ranking with implicit feedback has been steadily receiving more attention, mostly due to the "oneclass" characteristics of data in various services, e.g., "like" in Facebook and "bought" in Amazon. Previous works for solving this problem include pointwise regression methods based on absolute rating assumptions and pairwise ranking methods with relative score assumptions, where the latter was empirically found performing much better because it models users' ranking-related preferences more directly. However, the two fundamental assumptions made in the pairwise ranking methods, (1) individual pairwise preference over two items and (2) independence between two users, may not always hold. As a response, we propose a new and improved assumption, group Bayesian personalized ranking (GBPR), via introducing richer interactions among users. In particular, we introduce group preference, to relax the aforementioned individual and independence assumptions. We then design a novel algorithm correspondingly, which can recommend items more accurately as shown by various ranking-oriented evaluation metrics on four real-world datasets in our experiments.

Original languageEnglish
Title of host publicationIJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
PublisherAAAI press
Pages2691-2697
Number of pages7
ISBN (Print)9781577356332
Publication statusPublished - Aug 2013
Event23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China, Beijing, China
Duration: 3 Aug 20139 Aug 2013

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Country/TerritoryChina
CityBeijing
Period3/08/139/08/13

Scopus Subject Areas

  • Artificial Intelligence

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