Contents Recommendation Scheme Considering Trust and Collaborative Filtering in Online Social Networks

With the development of smartphones and online social networks, the users are creating and sharing a large amount of content. Concurrently, there have been recommendation schemes for providing users with content that matches their preferences. In this paper, we present a content recommendation scheme that uses trust-based user filtering. To perform user filtering, the trust of a user is determined by analyzing user social activities, content usage, and social relationships. In addition, trust of the content is considered to decide the content recommendation priority order. To calculate the content trust, we analyze the expertise of the user and implicit activities. It is shown through performance evaluation that the proposed scheme outperforms the existing scheme.