期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2014
卷号：3
期号：4
页码：1295-1298
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Large number of videos are available in online social network. User can directly access video contents in Online Social Network .It allowing user to import and re-shares the videos through the social connections. Video recommendation based on both content and social behaviour of user. It consists of four phases. They are (i) Data Collection, (ii) User Appearance, (iii) Similarity, and (iv) Clustering . Data Collection module consists of large number of videos from YouTube. From this videos the tag information are extracted and preprocessed the keyword. User Appearance based on User-User Matrix, Content-Content Matrix and Initial User-Content Matrix are computed. Missing entries in User -Content Matrix is update by using Social Propagation and Content Similarity. To find the similarity between User Space and Content Space is used to improve the high recommendation accuracy for importing and re-sharing. Finally, clustering with k- medoids to find the representative user and representative videos.
关键词：Online SocialNetwork; Content Similarity; ; Video Recommendation; Social Propagation
