Geo-Social K-Cover Group Queries For Collaborative Activity Planning
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.