Spatial Community Search Using PageRank Vector

摘要

Community detection task aims to find communities for a given network while community search focuses on finding a densely connected community with some given query nodes. Community search methods have the advantage of speed as they find a community for a set of query nodes instead of finding all the communities. They also have better performance on handling dynamic networks compared to community detection algorithms. However, current studies of community search are not well designed to handle spatial sensitive networks. We propose a new community search method, Spatial-based Search using PageRank Vector (SSPPV), which aims to find a community for a given query node over a large spatial social network. SSPPV finds a community with not only good cluster quality but also a smaller spatial size of the resulting community, compared to existing methods.