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KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System

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Methodologies for Knowledge Discovery and Data Mining (PAKDD 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1574))

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Abstract

A graph is one of the most common abstract structures and is suitable for representing relations between various objects. The analyzing system directly manipulating graphs is useful for knowledge discovery. Formal Graph System (FGS) is a kind of logic programming system which directly deals with graphs just like first order terms. We have designed and implemented a knowledge discovery system KD-FGS, which receives the graph data and produces a hypothesis by using FGS as a knowledge representation language. The system consists of an FGS interpreter and a refutably inductive inference algorithm for FGSs. We report some experiments of running KD-FGS and confirm that the system is useful for knowledge discovery from graph data.

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Author information

Authors and Affiliations

  1. Faculty of Information Sciences, Hiroshima City University, Hiroshima, 731-3194, Japan

    Tetsuhiro Miyahara, Tomoyuki Uchida, Kenichi Takahashi & Hiroaki Ueda

  2. Center for Collaborative Research, University of Tokyo, Tokyo, 153-0041, Japan

    Tetsuji Kuboyama

  3. Graduate School of Information Sciences, Hiroshima City University, Hiroshima, 731-3194, Japan

    Tatsuya Yamamoto

Authors
  1. Tetsuhiro Miyahara
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  2. Tomoyuki Uchida
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  3. Tetsuji Kuboyama
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  4. Tatsuya Yamamoto
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  5. Kenichi Takahashi
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  6. Hiroaki Ueda
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Systems Engineering, Yamaguchi University, Tokiwa-Dai, 2557, Ube, 755, Japan

    Ning Zhong

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Lizhu Zhou

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© 1999 Springer-Verlag Berlin Heidelberg

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Miyahara, T., Uchida, T., Kuboyama, T., Yamamoto, T., Takahashi, K., Ueda, H. (1999). KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System. In: Zhong, N., Zhou, L. (eds) Methodologies for Knowledge Discovery and Data Mining. PAKDD 1999. Lecture Notes in Computer Science(), vol 1574. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48912-6_58

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  • DOI: https://doi.org/10.1007/3-540-48912-6_58

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65866-5

  • Online ISBN: 978-3-540-48912-2

  • eBook Packages: Springer Book Archive

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