Extension of Graph-Based Induction for General Graph Structured Data

  • Takashi Matsuda
  • Tadashi Horiuchi
  • Hiroshi Motoda
  • Takashi Washio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1805)


A machine learning technique called Graph-Based Induction (GBI) efficiently extracts typical patterns from directed graph data by stepwise pair expansion (pairwise chunking). In this paper, we expand the capability of the Graph-Based Induction to handle not only tree structured data but also multi-inputs/outputs nodes and loop structure (including a self-loop) which cannot be treated in the conventional way. The method is verified to work as expected using artificially generated data and we evaluated experimentally the computation time of the implemented program. We, further, show the effectiveness of our approach by applying it to two kinds of the real-world data: World Wide Web browsing data and DNA sequence data.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Takashi Matsuda
    • 1
  • Tadashi Horiuchi
    • 1
  • Hiroshi Motoda
    • 1
  • Takashi Washio
    • 1
  1. 1.I.S.I.R.Osaka UniversityOsakaJapan

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