Exploiting spatial, temporal, and semantic information for point-of-interest recommendation - Yuan, Quan (2015)
With the prevalence of 3G & 4G services, people can easily share their opinions, moods, and activities with others via smartphones and tablets. As mobile devices are often GPS-enabled, a great quantity of user-generated content (UGC) with geographic locations has been accumulated, such as check-ins in location-based social networks (LBSNs), event-records in event-based social networks (EBSNs), and geo-annotated tweets on Twitter. Besides geographic location, UGC is often associated with timestamp and contains text content. The spatial, temporal and semantic information embedded in geo-annotated UGC can be exploited for a number of appealing applications and research problems. Point-of-interest (POI) recommendation is a representative one, which aims at recommending places that a target user has not visited before. Obviously, POI recommendation can help people explore new places and know their cities better. In addition, merchants can also benefit from it to deliver location-based advertisements and attract more customers.