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PReAmacy: A Personalized Recommendation Algorithm considering Contents and Intimacy between Users in Social Network Services  

Seo, Young-Duk (고려대학교 컴퓨터 전파통신공학과)
Kim, Jeong-Dong (고려대학교 컴퓨터 전파통신공학과)
Baik, Doo-Kwon (고려대학교 융합소프트웨어전문대학원)
Publication Information
Journal of KIISE:Databases / v.41, no.4, 2014 , pp. 209-216 More about this Journal
Abstract
Various characteristics of social network contents such as real-time, people relationship and big data can help to improve personalized recommender systems. Among them, 'people relationship' is a key factor of recommendation, so many personalized recommender systems utilizing it have been proposed. However, existing researches can not reflect personal tendency and are unable to provide precise recommendations in various domains, because they do not consider intimacy among people. In this paper, to solve these problems, we propose PReAmacy, a Personalized Recommendation Algorithm, considering intimacy among users and various characteristics of social network contents. Our experimental results indicate that not only the precision of PReAmacy is higher than that of existing algorithms, but intimacy is of great importance in PReAmacy.
Keywords
social network services; intimacy; personalized service; personalized recommender algorithm;
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