Exploiting Place Features in Link Prediction on Location-Based Social Networks
Link prediction systems have been largely adopted to recommend new friends in online social networks using data about social interactions. With the soaring adoption of location-based social services it becomes possible to take advantage of an additional source of information: the places people visit. In this paper the authors study the problem of designing a link prediction system for online location-based social networks. They have gathered extensive data about one of these services, Gowalla, with periodic snapshots to capture its temporal evolution.