Heterogeneous data fusion via matrix factorization for augmenting item, group and friend recommendations

Wei Zeng, Li CHEN

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

10 Citations (Scopus)

Abstract

Up to now, more and more social media sites have started to allow their users to build the social relationships. Take the Last.fm for example (which is a popular music-sharing site), users can not only add each other as friends, but also join interest groups that include people with common tastes. Therefore, in this environment, users might be interested in not only receiving item recommendations, but also friend recommendations whom they might consider putting in the contact list, and group recommendations that they may consider joining in. To support such needs, in this paper, we propose a generalized framework that provides three different types of recommendation in a single system: recommending items, recommending groups and recommending friends. For each type of recommendation, we in depth investigated the algorithm impact of fusing other two information resources (e.g., user-item preferences and friendship to be fused for recommending groups), along with their combined effect. The experiment reveals the ideal fusion mechanism for this multi-output recommender, and validates the benefit of factorization model for fusing bipartite data (such as membership and user-item preferences) and the benefit of regularization model for fusing one mode data (such as friendship). Moreover, the positive effect of integrating similarity measure into the regularization model is identified via the experiment.

Original languageEnglish
Title of host publication28th Annual ACM Symposium on Applied Computing, SAC 2013
Pages237-244
Number of pages8
DOIs
Publication statusPublished - 2013
Event28th Annual ACM Symposium on Applied Computing, SAC 2013 - Coimbra, Portugal
Duration: 18 Mar 201322 Mar 2013

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference28th Annual ACM Symposium on Applied Computing, SAC 2013
Country/TerritoryPortugal
CityCoimbra
Period18/03/1322/03/13

Scopus Subject Areas

  • Software

User-Defined Keywords

  • Friend recommendation
  • Group recommendation
  • Item recommendation
  • Matrix factorization
  • Regularization

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