Evaluating spam detection techniques using ranking algorithm in email network at Hanoi University
Keywords:Spam detection, email network, clustering, PageRank algorithm, user ranking
AbstractIn this paper, four spam-filtering approaches based on user ranking in the mail networks: Clustering, Extended Clustering Coefficient, PageRank Algorithm and Weighted PageRank Algorithm are analyzed. We also propose a couple of fully worked-out datasets from the email network of Hanoi University against which the experimental comparisons with the respect to the accuracy of email user ranking and spam filtering are conducted. The results indicate that PageRank Algorithm and Extended Clustering Coefficient approaches are better than others. The rate of true detection is over 99.5%, while the failed alarm remains below 0.5%.
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How to Cite
V. M. Tuan, T. Q. Anh, and H. Q. Minh, “Evaluating spam detection techniques using ranking algorithm in email network at Hanoi University”, JCC, vol. 30, no. 3, pp. 203–215, Aug. 2014.
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