Efficient Spam Post Detection by Compression-based Measure Using Suffix Trees

7 References
  • UEMURA Takashi
    Graduate School of Information Science and Technology, Hokkaido University
  • IKEDA Daisuke
    Department of Informatics, Graduate School of Information Science and Electrical Engineering Kyushu University
  • ARIMURA Hiroki
    Graduate School of Information Science and Technology, Hokkaido University

Bibliographic Information

Other Title
  • 接尾辞木を用いた圧縮尺度計算による効率よいスパムポスト検出手法

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Description

In this paper, we propose a content-based spam detection algorithm for blog spams and bulletin board spams. For a given document set D, our algorithm constructs a probabilistic model by using suffix trees, and detects spam documents in D. Experimental results showed that our algorithm performs well for detecting word salad spams, which are believed to be difficult to detect automatically.

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Details 詳細情報について

  • CRID
    1573668927312574720
  • NII Article ID
    110007100392
  • NII Book ID
    AN10012921
  • Text Lang
    ja
  • Data Source
    • CiNii Articles

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