Social group recommendation based on dynamic profiles and collaborative filtering

Recently, a number of studies on recommendation schemes over social network services have been actively conducted. In this paper, we propose a group recommendation scheme using users' profiles and collaborative filtering over social network. The proposed scheme updates profile information by collecting recent information on users' activities. Furthermore, it can recommend groups by utilizing the profile data of other users who are similar to a user in a group through collaborative filtering, thereby providing various groups to users. The profile information of the expert user has more weight than that of other users to consider expert information during group recommendation. It is shown through the performance evaluation that the proposed scheme provides various group recommendations in which users' changing preferences are considered sufficiently compared to the existing schemes.