Diversified utility maximization for recommendations

Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)

Abstract

Consider the problem of recommending items to a group of users subject to the diversity of their tastes. The goal is to recommend a list of items, such that the interests of each user are covered. We cast this problem as maximizing a diversified utility function of the group, the optimal solution of which can be found greedily. We conduct a user study in order to evaluate the performance of the proposed method. Evaluation results show that our method represents an effective strategy compared to various settings in which a convex combination of utility and diversity is maximized.
Original languageEnglish
Title of host publicationPoster-RecSys 2014
Subtitle of host publicationPoster Proceedings of the 8th ACM Conference on Recommender Systems (RecSys 2014)
EditorsLi Chen, Jalal Mahmud
PublisherCEUR Workshop Proceedings
Number of pages2
Publication statusPublished - 2014
Externally publishedYes
Event8th ACM Conference on Recommender Systems, RecSys 2014 - Silicon Valley, United States
Duration: 6 Oct 201410 Oct 2014

Conference

Conference8th ACM Conference on Recommender Systems, RecSys 2014
CountryUnited States
CitySilicon Valley
Period6/10/1410/10/14

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