An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data

  • Akihiro Inokuchi
  • Takashi Washio
  • Hiroshi Motoda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1910)

Abstract

This paper proposes a novel approach named AGM to efficiently mine the association rules among the frequently appearing sub-structures in a given graph data set. A graph transaction is represented by an adjacency matrix, and the frequent patterns appearing in the matrices are mined through the extended algorithm of the basket analysis. Its performance has been evaluated for the artificial simulation data and the carcinogenesis data of Oxford University and NTP. Its high efficiency has been confirmed for the size of a real-world problem....

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Akihiro Inokuchi
    • 1
  • Takashi Washio
    • 1
  • Hiroshi Motoda
    • 1
  1. 1.I.S.I.R.Osaka UniversityOsakaJapan

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