Exploring influence among participants for event recommendation

Event-based Social Networks (EBSN) are popular for organizing offline social events nowadays. In this paper, we develop a new model for event recommendation on EBSNs, which exploits the influence of existing participants, who have expressed willingness to join, on new participants in addition to other context information. Utilizing the participant influence can improve the effectiveness of event recommendation. Experiments on real datasets confirm that the consideration of participant influence can lead to more accurate prediction, offering better event recommendation.