Combining latent factor model with location features for event-based group recommendation

Groups play an essential role in many social websites which promote users' interactions and accelerate the diffusion of information. Recommending groups that users are really interested to join is significant for both users and social media. While traditional group recommendation problem has been extensively studied, we focus on a new type of the problem, i.e., event-based group recommendation. Unlike the other forms of groups, users join this type of groups mainly for participating offline events organized by group members or inviting other users to attend events sponsored by them. These characteristics determine that previously proposed approaches for group recommendation cannot be adapted to the new problem easily as they ignore the geographical influence and other explicit features of groups and users.