EventRec: Personalized Event Recommendations for Smart Event-Based Social Networks

In recent years, there has been a tremendous increase in the popularity of event-based social networks which allow social and physical interactions among their members. One major challenge for their members is the difficulty of searching events that meet their preferences from a large number of upcoming events. To tackle this challenge, we propose a personalized event recommendation framework called EventRec that exploits the geographical, social and temporal influences of events on users to generate personalized event recommendations. In EventRec, we model the influence of two-dimensional geographical location of an event using the Kernel Density Estimation method along with the popularity of the event location. Furthermore, the social influence in EventRec does not rely only on the relevance of a group to a user, but it also considers the relevance of the group to her friends. The geographical and social influences are integrated with the temporal influence that considers the preferences of the user and her friends on the days of the week and time of events. Our performance evaluation is conducted using two large Meetup.com data sets, and experimental results show that the quality of recommendations of EventRec outperforms the state-of-the-art event recommendation techniques.