摘要
针对传统社交网络社区划分算法普遍缺乏对节点属性、链接属性的综合考虑和充分表达利用节点与链接属性信息的模型和机制等问题,提出了一种融合节点与链接属性的社交网络社区划分算法。该算法融合节点属性的相似度、节点间链接权值等链接属性信息,定义了相似权值,并以此为基础,结合凝聚算法实现了对社交网络的社区划分。实验表明,该算法对社交网络中属性比较明显的社区划分效果显著。
The traditional social network community detection algorithms generally lack of consideration of node and link at- tributes, and full expression using node and link attribute information model and mechanism. Aiming at this issue, this paper put forward a kind of combined nodes and links attribute social network community detection algorithm. This algorithm combined with node attributes similarity between nodes, link weights and link information, defined the similar weights, and, on this basis, combining condensation algorithm to realize the social network of community division. Experiments show that effect of this algo- rithm about social network attribute is remarkable, obviously in attribute-distinct community.
出处
《计算机应用研究》
CSCD
北大核心
2013年第5期1477-1480,共4页
Application Research of Computers
基金
国家"863"计划资助项目(2011AA010603)
关键词
社交网络
社区划分
模块度
相似权值
social network
community detection
modularity
similar weight
