Skyline Group Queries in Large Road-social Networks Revisited

Abstract

Given a network with social and spatial information, cohesive group queries aim to find a group of strongly connected and closely co-located users. Most existing studies limit to finding groups with either the strongest social ties under certain spatial constraints or the minimum spatial distance under certain social constraints. It is difficult for users to decide which constraints they need to choose and how to prioritize the constraints to meet their real requirements since the social constraint and spatial constraint are different in nature. In this paper, we take a new approach to consider the constraints equally and study a skyline query. Specifically, given a road-social network consisting of a road network $G_r$ and a location-based social network $G_s$ , we aim to find a set of skyline cohesive groups, in which each group cannot be dominated by any other group in terms of social cohesiveness and spatial cohesiveness. The social cohesiveness is modeled by $(k, c)$ -core/truss (a k-core/truss of size c), and the spatial cohesiveness is evaluated by the total travel cost of meeting point from group members. We provide exact solutions and highly efficient greedy solutions for this problem.