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Discovery of Frequent Tag Tree Patterns in Semistructured Web Documents

  • Tetsuhiro Miyahara
  • Yusuke Suzuki
  • Takayoshi Shoudai
  • Tomoyuki Uchida
  • Kenichi Takahashi
  • Hiroaki Ueda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2336)

Abstract

Many Web documents such as HTML files and XML files have no rigid structure and are called semistructured data. In general, such semistructured Web documents are represented by rooted trees with ordered children. We propose a new method for discovering frequent tree structured patterns in semistructured Web documents by using a tag tree pattern as a hypothesis. A tag tree pattern is an edge labeled tree with ordered children which has structured variables. An edge label is a tag or a keyword in such Web documents, and a variable can be substituted by an arbitrary tree. So a tag tree pattern is suited for representing tree structured patterns in such Web documents. First we show that it is hard to compute the optimum frequent tag tree pattern. So we present an algorithm for generating all maximally frequent tag tree patterns and give the correctness of it. Finally, we report some experimental results on our algorithm. Although this algorithm is not efficient, experiments show that we can extract characteristic tree structured patterns in those data.

Keywords

Rooted Tree Term Tree Minimum Frequency Truth Assignment Edge Label 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Tetsuhiro Miyahara
    • 1
  • Yusuke Suzuki
    • 2
  • Takayoshi Shoudai
    • 2
  • Tomoyuki Uchida
    • 1
  • Kenichi Takahashi
    • 1
  • Hiroaki Ueda
    • 1
  1. 1.Faculty of Information SciencesHiroshima City UniversityHiroshimaJapan
  2. 2.Department of InformaticsKyushu UniversityKasugaJapan

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