微型电脑应用2025，Vol.41Issue(2)：174-177,4.
基于多层时序有偏PageRank算法的网络中关键节点数据挖掘
Data Mining of Key Nodes in Network Based on Multi-layer Temporal Biased PageRank Algorithm
吴凯 1张琦佳 1常晓润 1刘洋1
作者信息
- 1. 国网天津市电力公司信息通信公司,天津 300140
- 折叠
摘要
Abstract
This paper proposes the data mining method of key nodes in network based on the multi-layer temporal biased PageR-ank algorithm to mine network node data,so as to realize network key nodes mining.The temporal network is described by the connection relationship between the time layers and the nodes in the layer,based on which a multi-layer temporal network mod-el is built by similarity-based supra-adjacency matrix(SSAM)method.In the SSAM multi-layer temporal network model,the transition probability matrix of the network node is calculated based on the biased random walk process,and the next jump neighbor node of the walker is determined.The PageRank method is used to calculate the KeyRank value of the jump node de-termined by the transition probability matrix,and the importance ranking of the jump node in the multi-layer temporal network is completed according to the KeyRank value,so as to realize the key node mining in the multi-layer temporal network.The ex-periment results show that the proposed method can consider the similarity and difference between time layers and improve the accuracy of key node mining.关键词
多层时序网络/有偏PageRank算法/关键节点/数据挖掘/转移概率/KeyRank值Key words
multi-layer temporal network/biased PageRank algorithm/key node/data mining/transition probability/KeyRank value分类
信息技术与安全科学引用本文复制引用
吴凯,张琦佳,常晓润,刘洋..基于多层时序有偏PageRank算法的网络中关键节点数据挖掘[J].微型电脑应用,2025,41(2):174-177,4.
