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  • 标题:Review of Social Collaborative Filtering Recommender System’s Methods
  • 本地全文:下载
  • 作者:Pratibha Yadav ; Kumari Seema Rani ; Sonia Kumari
  • 期刊名称:International Journal of Engineering and Computer Science
  • 印刷版ISSN:2319-7242
  • 出版年度:2015
  • 卷号:4
  • 期号:10
  • 页码:14905-14910
  • DOI:10.18535/ijecs/v4i10.49
  • 出版社:IJECS
  • 摘要:Recommender Systems plays a vital role in e-commerce. The goal of recommender system is to present theuser with the personalized information that matches with the user’s interest. Now a days, user’s interest isleaning towards social networks. Social Networking Sites provide users a platform to connect and share theirinformation with other users who share similar interests with user. The popularity of social networking sitesis increasing day by day. Recommender systems are now using the social information for their analysis andprediction process. Collaborative filtering approach is assumed to be the broadly approved technique ofrecommender system. Collaborative filtering method recommends an item to a user based on the preferencesof other users who share analogous interest with the active user. In this paper, we have presented a study ofcollaborative filtering based social recommender system.
  • 关键词:Recommender System; Collaborative Filtering; Social Collaborative Filtering
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