期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2016
卷号：39
期号：3
页码：29
出版社：IEEE Computer Society
摘要：The proliferation of rich information available for real world entities and their relationships gives riseto a type of graph, namely attributed graph, where graph vertices are associated with a number ofattributes. The set of an attribute can be formed by a series of keywords. In attributed graphs, itis practically useful to discover communities of densely connected components with homogeneous at-tribute values. In terms of different aspects, the community analysis tasks can be categorized into globalnetwork-wide and ego-centric personalized. The global network-wide community analysis considers theentire network, such that community detection, which is to find all communities in a network. On theother hand, the ego-centric personalized community analysis focuses on the local neighborhood sub-graph of given query nodes, such that community search. Given a set of query nodes and attributes,community search in attributed graphs is to locally detect meaningful community containing query-related nodes in the online manner. In this work, we briefly survey several state-of-the-art communitymodels based on various dense subgraphs, meanwhile also investigate social circles, that one specialkind of communities are formed by friends in 1-hop neighborhood network for a particular user.
