An overlapping community structure detecting algorithm in semantic social network based on block field

作者：Xin, Yu; Yang, Jing^*; Xie, Zhi Qiang

来源：Acta Automatica Sinica, 2015, 41(2): 362-375.

DOI：10.16383/j.aas.2015.c140136

• Community detection
• Community detection algorithms
• Experimental analysis
• Latent dirichlet allocations
• Overlapping communities
• Semantic information
• Semantic social networks
• Topological relationships

The semantic social network (SSN) is a new kind of complex networks consisting of the node content and topological relationship. The traditional community detection algorithms need to preset the number of the communities and could not detect the overlapping communities. To solve this problem, an overlapping community structure detecting algorithm in semantic social network based on the block field is proposed. Firstly, it takes the latent dirichlet allocation (LDA) model as the semantic analyzing model, establishing the block-author-topic (BAT) model with the sampling node as the core node. Secondly, it suggests the measurement of the semantic cohesion of the block field, depending on the analysis of SSN, to achieve the evaluation of semantic information. Finally, it improves the label propagation algorithm (LPA) which could detect the overlapping communities, with the semantic cohesion as input, and designs the SQ measurement modularity for semantic measuring. The efficiency and feasibility of the algorithm and the semantic modularity are verified via experimental analysis.

• 出版日期2015
• 单位哈尔滨工程大学