Knowledge Discovery in Geo-Social Networks to Provide a Location Recommending Service

The increasing availability of location-acquisition technologies like GPS has enabled people to record their location history and sharing it on internet. Using this capability in web based social networks and considering the shared spatio-temporal data as edge that connects users of social networks to spatial data layer, has resulted geo-social networks. The dimension of location brings social networks back to reality, bridging the gap between the physical world and online social networking services. With the huge amount of frequently updated information from all around the world, geo-socialnetworks are rich sources for data mining which can be used in providing different efficient location based services and improving user's social relations structure. In this paper we aim to mine interesting locations, attractive travel sequences and expert users in a given geospatial region according to multiple user's shared checkin data that has been modeled with a hierarchical uniform framework. At the end, by using discovered knowledge, a service that will offer location for visiting according to the user's spatio - temporal query has been represented.