基于LeaderRank和节点相似性的多标签传播重叠社团挖掘算法  

Multi-Label Propagation Algorithm for Overlapping Community Detection Based on LeaderRank and Node Similarity

作　　者：王林[1] 饶仁杰 WANG Lin;RAO Ren-Jie(College of Automation and Information Engineering, Xi＇an University of Technology, Xi＇an 710048, China)

机构地区：[1]西安理工大学自动化与信息工程学院,西安710048

出　　处：《计算机系统应用》2018年第6期146-150,共5页Computer Systems & Applications

基　　金：陕西省科技计划重点项目(2017ZDCXL-GY-05-03)

摘　　要：针对基于多标签传播重叠社团挖掘算法COPRA因随机更新策略带来的不稳定性以及需要预先输入参数的局限性等问题,提出一种基于LeaderRank和节点相似性的多标签传播重叠社团挖掘算法.该算法首先利用LeaderRank算法对网络中的节点进行重要性排序从而确定节点的更新顺序,减少标签不必要的更新.在标签传播过程中,根据节点相似性重新设计标签的更新策略,提高算法的稳定性.将算法应用于人工网络和真实网络中进行实验,实验结果表明该算法在挖掘重叠社团上具有较高的准确性和稳定性.The defects of overlapping community detection algorithm COPRA based on multi-label propagation include instability and pre-parameter limits, this study proposed a multi-label propagation algorithm for overlapping community detection based on Leader Rank and the node similarity. The algorithm uses the Leader Rank algorithm to sort the nodes in the network to determine the order of nodes updating. Then, re-design the label update strategy according to the similarity of nodes to improve the stability of the algorithm. The algorithm is applied to the artificial network and the real networks.The experimental results show that the proposed algorithm has high accuracy and stability for detecting overlapping communities.

关 键 词：复杂网络 重叠社团挖掘 多标签传播算法 LeaderRank算法 节点相似性 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]