Location-aware group preference queries in social-networks

With the recent advances in location-acquisition techniques and GPS-embedded mobile devices, traditional social networks such as Twitter and Facebook have acquired the dimension of location. This in result has facilitated the generation of geo-tagged data (e.g., check-ins) at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Typical location-based social networks allow people to check-in at a location of interest using smart devices which then is published on social network and this information can be exploited for recommendation. In this paper, we propose a new type of query called Geo-Social Group preference Top-k (SG-Top_k) query. For a group of users, a SG-Top_k query returns top-k places that are most likely to satisfy the needs of users based on spatial and social relevance. Finally, we conduct an exhaustive evaluation of proposed schemes to answer the query and demonstrate the effectiveness of the proposed approaches.