Email Network Important Nodes Mining Using Core Number and PageRank

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.