Context-Aware Event Recommendation in Event-based Social Networks

The Web has grown into one of the most important channels to communicate social events nowadays. However, the sheer volume of events available in event-based social networks (EBSNs) often undermines the users’ ability to choose the events that best fit their interests. Recommender systems appear as a natural solution for this problem, but differently from classic recommendation scenarios (e.g. movies, books), the event recommendation problem is intrinsically cold-start. Indeed, events published in EBSNs are typically short-lived and, by definition, are always in the future, having little or no trace of historical attendance. To overcome this limitation, we propose to exploit several contextual signals available from EBSNs. In particular, besides contentbased signals based on the events’ description and collaborative signals derived from users’ RSVPs, we exploit social signals based on group memberships, location signals based on the users’ geographical preferences, and temp...

• Type: Journal
• Year: 2015
• Where: RECSYS
• Authors: Augusto Q. de Macedo, Leandro Balby Marinho, Rodrygo L. T. Santos
• Keywords: Control Systems, RECSYS 2015