Semantic tagging of places based on user interest profiles from online social networks

In recent years, location based services (LBS) have become very popular. The performance of LBS depends on number of factors including how well the places are described. Though LBS enable users to tag places, users rarely do so. On the other hand, users express their interests via online social networks. The common interests of a group of people that has visited a particular place can potentially provide further description for that place. In this work we present an approach that automatically assigns tags to places, based on interest profiles and visits or check-ins of users at places. We have evaluated our approach with real world datasets from popular social network services against a set of manually assigned tags. Experimental results show that we are able to derive meaningful tags for different places and that sets of tags assigned to places are expected to stabilise as more unique users visit places.