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A comparative definition of Community and Corresponding Identifying Algorithm

A Comparative Definition of Community and Corresponding Iden...

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第四届全国网络科学学术论坛暨研究生暑期学校

作者： Yanqing Hu Hongbin Chen Peng Zhang Menghui Li Zengru Di Ying Fan~* Department of Systems Science,School of Management.Center for Complerity Research,Baijing Normal University,Beijing 100875,P.R.China

＜正＞In this paper,a comperstive definition for community in networks is proposed and the corresponding detecting in given. A community is defined as a set of nodes,which satisfy that each node’s degree inside the community should not be smaller than the node’s degree toward any other community. In the algorithm,the sttractive force of a community to a node is defined as the connections between *** employing sttractive force based self-organizing process,without any extra parameter, the best communities can be *** artificial and real-world networks,including Zachary Karate chub network,Gollege football notwork and large Scientific collsboration network are *** algorithm works well in detecting communities and it also gives a nice deecription for network division and group formation.

关键词： Complex Network Community Structure comparative definition

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A Fast Method for Community Detection Based on the Contribution of Nodes

A Fast Method for Community Detection Based on the Contribut...

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2011 International Conference on Computer Science and Information Technology(ICCSIT 2011)

作者： Xiangtao Chen Houwang Xing School of Information Science and Engineering Hunan University

ISBN: (纸本)9781612848334

Communities exist in complex network of different areas, and there have been some methods to identify the communities in networks. However, the high computationally demanding limits their applications. In this paper, we propose a measurement of relationship between node and community, and then give a new comparative definition for community in complex networks. Based on these definitions we put forward the corresponding detecting algorithm. The effectiveness of our algorithm is demonstrated by extensive experiments on lots of computer generated graphs and public available real-world graphs. The result shows our algorithm is fast and accuracy in detecting communities.

关键词： comparative definition Community Structure Contribution Complex Network

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