The User-Group Based Recommendation for the Diverse Multimedia Contents in the Social Network Environments

It has become general that consumers freely create contents and spend them for themselves on Web services in Web 2.0 environments. This research introduces the personalized contents recommendation system that answers the recent propensity trends about the multimedia contents based on web environments. The proposed system mined the usage history patterns of the target user and the related users from the web and proposed users´ favorable contents which are unknown to users. The Social relationships in social network environments help the system to gather the meaningful history for users. And the system also recommended the various multimedia contents - articles, TV programs, advertisements, video and audio, the system could apply the various users´ history about the various contents. Because the system is applied to the social network environments, the information about friends and groups can be used in the recommendation algorithm.