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Collaborative Filtering Techniques Using Social Network Analysis for UCC Recommendation  

Jeong, Joong-Hee (한양대학교 경영학과)
Kim, Jong-Woo (한양대학교 경영대학 경영학부)
Publication Information
The Journal of Korean Institute of Information Technology / v.11, no.1, 2013 , pp. 185-195 More about this Journal
Abstract
In this study, a collaborative filtering (CF) based recommendation method which uses social network analysis measures is proposed and tested empirically to improve the performance of recommendation. Current CF techniques recommend appropriate product information to customers based on users' preference similarity. The proposed method uses centrality measures which can be obtained from user social network with user' preference similarity to select appropriate product information for users. The recommendation performance of the proposed method is compared with that of current CF empirically. To test performance empirically, user visiting web log data of www.youtube.com which is a representative UCC (User Created Contents) site is used. The experimental results show that the combined usage of social network analysis measures can contribute to improve recommendation performance.
Keywords
recommender system; collaborative filtering; social network analysis;
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Times Cited By KSCI : 3  (Citation Analysis)
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