Co-Engaged Location Group Search in Location-Based Social Networks.

Searching for well-connected user communities in a Location-based Social Network (LBSN) has been extensively investigated. However, very few studies focus on finding a group of locations in an LBSN which are significantly engaged with socially cohesive user groups. In this work, we investigate the problem of C o-engaged L ocation group S earch ( CLS ) from LBSNs where the selected locations are visited frequently by the members of the socially cohesive user groups, and the locations are reachable within a given distance threshold. To the best of our knowledge, this is the first work to search for socially co-engaged location groups in LBSNs. We devise a score function to measure the co-engagement of the location groups by combining social connectivity of the cohesive user groups and check-in density of the users to the selected locations. To solve the CLS problem, we propose a Filter-and-Verify algorithm that effectively filters out ineligible locations, and their corresponding check-in users. Further, we derive a lower bound on the number of check-ins to prune the insignificant locations and develop a novel greedy forward expansion algorithm ( GFA ). To accelerate the computation of CLS , we propose a ranking function and devise an incremental algorithm, GIA , that can filter the unqualified location groups. We establish the effectiveness of our solutions by conducting extensive experiments on three real-world datasets.