A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems

Oluwasanmi Koyejo, Joydeep Ghosh

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

Abstract

Pairwise interaction networks capture inter-user dependencies (e.g. social networks) and inter-item dependencies (e.g item categories) that provide insight into user and item behavior. It is often assumed that such interaction information is informative for preference prediction. This may not be the case, as the some of the observed interactions may not be correlated with the preferences, and their use may negatively impact performance by introducing undesired noise. We propose an approach for weighting each interaction, such that we can determine the importance of each interaction to the preference prediction task. We model the preferences using kernel matrix factorization; where the kernels capture the weighted effects of the interactions. Our approach is validated on Last.fm and Movielens datasets; which include multiple sources of explicit and implicit interuser and inter-item interactions. Our experiments suggest that learning the most important interactions can improve recommendation performance when compared to the standard matrix factorization approach.

Original languageEnglish (US)
Title of host publicationProceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011
Pages9-16
Number of pages8
DOIs
StatePublished - Nov 23 2011
Externally publishedYes
Event2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011 - Chicago, IL, United States
Duration: Oct 27 2011Oct 27 2011

Publication series

NameProceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011

Other

Other2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011
CountryUnited States
CityChicago, IL
Period10/27/1110/27/11

ASJC Scopus subject areas

  • Information Systems

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    Koyejo, O., & Ghosh, J. (2011). A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems. In Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011 (pp. 9-16). (Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec 2011 - Held at the 5th ACM Conference on Recommender Systems, RecSys 2011). https://doi.org/10.1145/2039320.2039322