基于信息嫡的社区发现算法研究

计算机科学 ›› 2011, Vol. 38 ›› Issue (2): 238-240.

基于信息嫡的社区发现算法研究

王刚，钟国祥

(安康学院电子与信息工程系　安康725000)　(重庆教育学院科技处　重庆400067)

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受陕西省教育厅项目(09JK317)，基于本体的服务研究(AYQDZR200916) ,智能信息处理技术关键问题及应用研究(2008akxy005)资助。

Study on Algorithm of Community Detection Based on Information Entropy

WANG Gang,ZHONG Guo-xiang

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 针对现有社区发现依靠出度、入度、介数来进行社会划分的一些不足，研究了依靠信息嫡来对社区进行度量，提出了基于信息嫡的社区发现算法CD13E(Community Detection Based on Entropy)。如果社区内部信息量大，嫡就大。不确定事件发生的概率就大。社区具有凝聚力，信息的嫡相对稳定，不会出现嫡剧烈增加或减少的情况，根据节点集合墒的变化是否剧烈，可以判断节点是否是社区的成员，从而实现社区的发现。实验表明，CDBE能够发现有价值的社区。

关键词: 社区发现，信息嫡，推荐系统，数据挖掘

Abstract: There are some faults of present community detection algorithm, which is based on the in degree, out degree and betweenness of nodes,we presented a algorithm based on Entropy to detect community structure. A community ineludes many information and it's Entropy. Members of a community have some common gains or interests, we think that if a member want to join a community, it can't make the entropy of the community exceed a threshold, otherwise it can't be the member of a exist community. Our experiments show the processing and the efficiency of our algorithms.

Key words: Community detection, Information entropy, Recommendation system, Data mining

王刚，钟国祥. 基于信息嫡的社区发现算法研究[J]. 计算机科学, 2011, 38(2): 238-240. https://doi.org/

WANG Gang,ZHONG Guo-xiang. Study on Algorithm of Community Detection Based on Information Entropy[J]. Computer Science, 2011, 38(2): 238-240. https://doi.org/

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