Overlapping Community Detection Based on Node Importance and Adjacency Information
Overlapping Community Detection Based on Node Importance and Adjacency Information
复制标题
基于节点重要性和邻接信息的重叠社区检测
DOI：
10.1155/2021/8690662
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发表时间：
2021-12
影响因子：
--
通讯作者：
Yangyang Lu
中科院分区：
文献类型：
--
作者：
Ping Wang;Yonghong Huang;Fei Tang;Hongtao Liu;Yangyang Lu
Detecting the community structure and predicting the change of community structure is an important research topic in social network research. Focusing on the importance of nodes and the importance of their neighbors and the adjacency information, this article proposes a new evaluation method of node importance. The proposed overlapping community detection algorithm (ILE) uses the random walk to select the initial community and adopts the adaptive function to expand the community. It finally optimizes the community to obtain the overlapping community. For the overlapping communities, this article analyzes the evolution of networks at different times according to the stability and differences of social networks. Seven common community evolution events are obtained. The experimental results show that our algorithm is feasible and capable of discovering overlapping communities in complex social network efficiently.
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2014
期刊：
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影响因子：
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通讯作者：
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影响因子：
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