基于核心数和PageRank的电子邮件网络重要节点挖掘

Xianghui Zhao, Zhirong Li, Junkai Yi
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引用次数: 0

摘要

挖掘重要人物对计算机网络安全,特别是电子邮件网络集中化的研究具有重要意义。传统的PageRank算法由于PR值分布均匀,对网络干扰比较敏感。本文提出了一种基于核心数将电子邮件网络分层的方法,消除了外层的干扰节点,减少了干扰节点的影响,降低了后续处理的复杂性。对PageRank算法进行改进,部分解决了节点权重偏差问题,对节点进行定量排序,找到重要节点。实验表明,该方法提高了邮件网络重要节点挖掘的准确性,降低了计算复杂度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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