自动化学报Issue(10)：2262-2275,14.DOI:10.3724/SP.J.1004.2014.02262
基于标签传播的语义重叠社区发现算法
An Overlapping Semantic Community Structure Detecting Algorithm by Label Propagation
摘要
Abstract
Since the semantic social network (SSN) is a new kind of complex networks consisting of information nodes and link relationships, the traditional community detection algorithms which depend on the adjacency in social networks are not efficient in the SSN. To solve this problem, an overlapping community structure detecting method in semantic social network is proposed based on label propagation. Firstly, the algorithm utilizes the Gibss sampling method to establish the quantization mapping by which semantic information in nodes can be mapped into the semantic space, with the latent Dirichlet allocation (LDA) as the semantic model. Secondly, a principal component SCNP model is proposed which could measure the propinquity between nodes and the semantic impact model. Thirdly, an improved semantic label propagation algorithm is put forward, with SCNP as the weight of propagation and SI as the parameter of threshold. Finally, a semantic model by which the community structure of SSN can be measured is presented. The efficiency and feasibility of the algorithm and the semantic modularity are verified by experimental analysis.关键词
语义社会网络/重叠社区/LDA模型/标签传播算法Key words
Semantic social network (SSN)/overlapping community/latent Dirichlet allocation (LDA)/label propagation algorithm (LPA)引用本文复制引用
辛宇,杨静,谢志强..基于标签传播的语义重叠社区发现算法[J].自动化学报,2014,(10):2262-2275,14.基金项目
国家自然科学基金(61370083,61073043,61073041,61370086,61402126),国家教育部博士点基金(20112304110011,20122304110012)资助Supported by National Natural Science Foundation of China (61370083,61073043,61073041,61370086,61402126) and Na-tional Research Foundation for the Doctoral Program of Higher Education of China (20112304110011,20122304110012) （61370083,61073043,61073041,61370086,61402126）
