计算机工程2016，Vol.42Issue(12)：196-203,8.DOI:10.3969/j.issn.1000-3428.2016.12.034
一种基于局部相似性的社区发现算法
A Community Detection Algorithm Based on Local Similarity
摘要
Abstract
Many existing community detection algorithms focus on topological structure or node attributes.Some attribut graph clustering algorithms consider both of them but the quality of community is not good.Shared neighbors based local similarity algorithms underestimate pairwise of node similarity.Hence,this paper proposes a new Local Similarity based Community Detection(LS-CD)algorithm.The proposed algorithm contains two main components:node local similarity calculation and node clustering.It evaluates the vertex importance using the Pagerank algorithm and calculates the similarity of pairwise vertexes by combining connetion strength and node attribute.To avoid underestimating node similarity based on shared neighbors,the similarity of vertexes is calculated by the similarity of their local neighborhoods.The K-Medoids clusteringalgorithmisusedtoidentifycommunitybymeasuringthelocalsimilarityofnodeandclustercentroid.Experimentalresultsshowthat,comparedwithtraditionalSA-Clusterandk-SNAPalgorithms,thisalgorithmcanminehighqualitycommunityandhasgoodcommunityidentificationeffect.关键词
社区发现/图聚类/属性图/节点重要性/局部相似性/节点相似度Key words
community detection/graph clustering/attributed graph/node importance/local similarity/node similarity分类
信息技术与安全科学引用本文复制引用
吴钟刚,吕钊..一种基于局部相似性的社区发现算法[J].计算机工程,2016,42(12):196-203,8.基金项目
上海市科学技术委员会科研计划项目(1451110700,14511106803) （1451110700,14511106803）
上海市张江国家自主创新示范区专项发展资金(201411-JA-B108-002). （201411-JA-B108-002）
