Title
A Progressive Approach for Neighboring Geosocial Communities Search Over Large Spatial Graphs
Abstract
Searching for neighbors for a query node in a spatial network is a fundamental problem and has been extensively investigated. However, most existing works focus only on the node level when conducting such a query and rarely pay attention to the social relations among the neighbors. We argue that a user, in some cases, is more likely to engage in some activities collectively, i.e., going to the bar with friends rather than alone. For this reason, we consider the neighbor searching problem at a community level in this paper and examine a new problem: Neighboring Geosocial Communities Search (NGCS) over large spatial graphs. Specifically, given a parameter n and query node q, we aim to find the top-n nearest communities for q. Moreover, in each returned community, nodes have cohesive relations with each other and are covered by a minimum covering circle (MCC) whose radius is less than r. It is obvious that the NGCS problem finds its standard applications in marketing and other scenarios but it is very challenging for large spatial graphs because it requires detecting all qualified cohesive user communities. Therefore, in this paper, we adopt a local search approach to reduce the difficulty. The introduced algorithm finds the top-n neighboring geo-social communities through a progressive search in the graph without thoroughly examining the graph. Analyses show that the complexity of the algorithm is decreased by an order of magnitude. Extensive experiments on real social networks confirm the superiority and effectiveness of our solutions.
Year
DOI
Venue
2022
10.1109/ACCESS.2022.3168361
IEEE ACCESS
Keywords
DocType
Volume
Social network services, nearest neighbor searches, spatial network
Journal
10
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Zewen Wu100.34
Jian Xu222455.55
Huaixiang Zhang300.34
Qing Bao400.34
Qing Sun500.34
Changbeng Zhou600.34