A Novel Iterative Algorithm for Community Division Based on Node Similarity
Social networks are a hot topic on Internet and are paid more attentions to.In social networks,each community unit contains much valuable information.The community division has become an important subject of social networks.So far,many researchers have achieved a lot.But,more efficient methods for community division are still needed.In this paper,on the consideration of each node property in the social networking,we develop a novel iterative algorithm of the community division which is based on node similarity through the analysis of similarities between nodes and the node”s proximity relationship with the community.The experimental evaluation of Zachary”s Karate Club and Dolphin networks the community networks indicate that the algorithm mentioned in this paper is very close to actual Social Networking and it has reliable division accuracy.Compared with the GN algorithm and FN algorithm,the proposed algorithm has improved the accuracy.
Social Network Community division Node similarity Iteration
Feng HU Hua-Bin LOU Jie-Xian DENG
Chongqing Key Laboratory of Computational Intelligence,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
国内会议
杭州
英文
1-6
2014-10-18（万方平台首次上网日期，不代表论文的发表时间）