Abstract: EBSN(Event-based Social Networks) not only contain online social interactions in the conventional online social networks,but also include valuable offline social interactions captured in offline activities,possessing a complicated heterogeneous nature.How to use the coexistence of online and offline social interactions to improve the service quality has become a hot issue in both academic and industry domains.Besides considering basic attributes from events and users, most traditional social activity recommendation approaches recommend interesting activities to users based on explicit friendships.However,there is no explicit friendships in EBSN,which makes these traditional algorithms can’t be applied to EBSN’s event recommendation directly.In this light,a novel concept LF (Latent Friendship) was defined in this paper.LF not only takes into account the online same group relationships,but also considers the offline same activity relationships.Further,ARLF(Activity Recommendation Algorithm based on Latent Friendship)was proposed by synthesizing the influence of group and activity for activity recommendation.Meanwhile,this paper creatively applied the idea of Meta-Path to capture the latent friends,which exploits the heterogeneous information fully in EBSN.Finally,extensive experiments based on real data of Meetup show that ARLF is feasible and effective on recommending desirable and interesting activities for EBSN users.

Key words: EBSN,Online interactions,Offline interactions,Latent friendships,Meta-path,Activity recommendation