摘要： 针对目前社会网络中单属性识别的局限性、多属性识别中属性选取的主观性和识别结果不准确的缺点,提出一种综合识别方法。从多目标优化问题出发,综合社会网络和系统科学的分析方法识别核心节点集,并使用多个经典决策属性通过二次评价的方法提高算法的精度。在美国APRA网络和Zachary空手道俱乐部网络上的实验结果表明,该方法能够有效提高社会网络中核心节点集的识别准确率。

关键词: 社会网络, 核心节点, 决策属性, 多目标优化, 二次评价

Abstract: Against the problems that most of the existing single attribute recognition is limited and the subjectivity during attribute selection of multiple attribute recognition in social network,this paper proposes a perspective method for core node recognition.Based on optimizing multiple objective of interest,it combines the analysis of social network and system science.Then,combining with multiple classical decision attributes,it uses reevaluation to improve the accuracy of the algorithm.Experimental results in the ARPA and Zachary’s karate club network show that the proposed method can improve the recognition rate of core node sets in social network.

Key words: social network, core node, decision attribute, multiple objective optimization, reevaluation

中图分类号: 

• TP18