电子科技大学学报Issue(6)：898-903,6.DOI:10.3969/j.issn.1001-0548.2014.06.018
基于概率主题模型的社交网络层次化社区发现算法
Hierarchical Community Discovery for Social Networks Based on Probabilistic Topic Model
摘要
Abstract
The traditional community discovery algorithms are generally based on the link structure of a given social network, they lack of consideration of user’s interests and the hierarchical structure of community. In this paper, a novel PAM (Pachinko Allocation Model) probabilistic generative model is proposed to detect latent hierarchical communities based on the user interests and their social relationships. The joint model of topic modeling and community discovery can capture the correlation among multiple communities and their hierarchical structure. Experiments on real-world dataset have confirmed the feasibility and effectiveness of the proposed algorithm.关键词
层次化社区发现/LDA/概率生成模型/社交网络Key words
hierarchical community discovery/LDA/probabilistic generative model/social network分类
信息技术与安全科学引用本文复制引用
毕娟,秦志光..基于概率主题模型的社交网络层次化社区发现算法[J].电子科技大学学报,2014,(6):898-903,6.基金项目
国家高技术研究发展计划(2011AA010706)；国家自然科学基金(61133016) （2011AA010706）
