6533b858fe1ef96bd12b5796
RESEARCH PRODUCT
Cross-Social Network Collaborative Recommendation
Alexander SemenovTat-seng ChuaDenis KotkovAleksandr FarseevJari Veijalainensubject
World Wide WebSocial networkComputer sciencebusiness.industryRecommender systembusinessdescription
Online social networks have become an essential part of our daily life, and an increasing number of users are using multiple online social networks simultaneously. We hypothesize that the integration of data from multiple social networks could boost the performance of recommender systems. In our study, we perform cross-social network collaborative recommendation and show that fusing multi-source data enables us to achieve higher recommendation performance as compared to various single-source baselines.
year | journal | country | edition | language |
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2015-06-28 | Proceedings of the ACM Web Science Conference |