Exploring implicit hierarchical structures for recommender systems

Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

42 Scopus citations

Abstract

Items in real-world recommender systems exhibit certain hierarchical structures. Similarly, user preferences also present hierarchical structures. Recent studies show that incorporating the explicit hierarchical structures of items or user preferences can improve the performance of recommender systems. However, explicit hierarchical structures are usually unavailable, especially those of user preferences. Thus, there's a gap between the importance of hierarchical structures and their availability. In this paper, we investigate the problem of exploring the implicit hierarchical structures for recommender systems when they are not explicitly available. We propose a novel recommendation framework HSR to bridge the gap, which enables us to capture the implicit hierarchical structures of users and items simultaneously. Experimental results on two real world datasets demonstrate the effectiveness of the proposed framework.

Original languageEnglish (US)
Title of host publicationIJCAI International Joint Conference on Artificial Intelligence
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1813-1819
Number of pages7
Volume2015-January
ISBN (Print)9781577357384
StatePublished - 2015
Event24th International Joint Conference on Artificial Intelligence, IJCAI 2015 - Buenos Aires, Argentina
Duration: Jul 25 2015Jul 31 2015

Other

Other24th International Joint Conference on Artificial Intelligence, IJCAI 2015
CountryArgentina
CityBuenos Aires
Period7/25/157/31/15

ASJC Scopus subject areas

  • Artificial Intelligence

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    Wang, S., Tang, J., Wang, Y., & Liu, H. (2015). Exploring implicit hierarchical structures for recommender systems. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2015-January, pp. 1813-1819). International Joint Conferences on Artificial Intelligence.