Paper Title
Geo-Social K-Cover Group Queries For Collaborative Activity Planning

Abstract
Good amount of personal information is available due to fast growth and development of ubiquitous internet access, location- aware mobile devices and social computing technologies, hence location data and social data from various mobile platforms and online social networks are readily available and accessible. The combination or convergence of these two types of data that is, location data and social data is known as geo-social data. This convergence has enabled collaborative spatial computing, which means explicit combination of location and social factors to answer our required useful geo-social queries for either the purpose of social good or business such as group decision making travel recommendation and spatial task outsourcing. In this paper, A new type of query known as Geo-Social K- Cover Group(GSKCG) queries is utilized. This query takes the given set of query points and social network, retrieve a user group, a minimum group where each user socially has social relation to at least K other users and users familiar regions, so that social relations and associated regions jointly cover all the query points. We slowly explore effective pruning strategy to derive optimal solution group with an efficient algorithm. To accelerate the query processing we further design a novel index structure. Finally with efficient pruning strategy and novel index structure, a minimum user group which covers all the query points is retrieved. Keywords— Location-Based Services, Query Processing, Social Constraints, Group Queries.