{"title":"基于核心数和PageRank的电子邮件网络重要节点挖掘","authors":"Xianghui Zhao, Zhirong Li, Junkai Yi","doi":"10.1109/ICISCE.2016.87","DOIUrl":null,"url":null,"abstract":"Mining important persons is significant to computer network and security, especially researches on email network centralization nowadays. Traditional PageRank algorithm is sensitive to the network disturbance because it distributes PR values evenly. This paper proposes a method which decomposes email network into different layers based on the core number, eliminates the interferential nodes from outer layers to decrease impact of interferential nodes and complexity of following procedure. Besides, it improves PageRank algorithm so as to partially solve the bias problem on nodes' weighting, rank the nodes quantitatively to find the important nodes. The experiments indicate that it improves the accuracy and reduces the computational complexity in mining important nodes from email network.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":"1 1","pages":"363-367"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Email Network Important Nodes Mining Using Core Number and PageRank\",\"authors\":\"Xianghui Zhao, Zhirong Li, Junkai Yi\",\"doi\":\"10.1109/ICISCE.2016.87\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mining important persons is significant to computer network and security, especially researches on email network centralization nowadays. Traditional PageRank algorithm is sensitive to the network disturbance because it distributes PR values evenly. This paper proposes a method which decomposes email network into different layers based on the core number, eliminates the interferential nodes from outer layers to decrease impact of interferential nodes and complexity of following procedure. Besides, it improves PageRank algorithm so as to partially solve the bias problem on nodes' weighting, rank the nodes quantitatively to find the important nodes. The experiments indicate that it improves the accuracy and reduces the computational complexity in mining important nodes from email network.\",\"PeriodicalId\":6882,\"journal\":{\"name\":\"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)\",\"volume\":\"1 1\",\"pages\":\"363-367\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCE.2016.87\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCE.2016.87","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Email Network Important Nodes Mining Using Core Number and PageRank
Mining important persons is significant to computer network and security, especially researches on email network centralization nowadays. Traditional PageRank algorithm is sensitive to the network disturbance because it distributes PR values evenly. This paper proposes a method which decomposes email network into different layers based on the core number, eliminates the interferential nodes from outer layers to decrease impact of interferential nodes and complexity of following procedure. Besides, it improves PageRank algorithm so as to partially solve the bias problem on nodes' weighting, rank the nodes quantitatively to find the important nodes. The experiments indicate that it improves the accuracy and reduces the computational complexity in mining important nodes from email network.