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Mining Propositional Knowledge Bases to Discover Multi-level Rules

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Mining Multimedia and Complex Data (PAKDD 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2797))

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Abstract

This paper explores how knowledge in the form of propositions in an expert system can be used as input into data mining. The output is multi-level knowledge which can be used to provide structure, suggest interesting concepts, improve understanding and support querying of the original knowledge. Appropriate algorithms for mining knowledge must take into account the peculiar features of knowledge which distinguish it from data. The most obvious and problematic distinction is that only one of each rule exists. This paper introduces the possible benefits of mining knowledge and describes a technique for reorganizing knowledge and discovering higher-level concepts in the knowledge base. The rules input may have been acquired manually (we describe a simple technique known as Ripple Down Rules for this purpose) or automatically using an existing data mining technique. In either case, once the knowledge exists in propositional form, Formal Concept Analysis is applied to the rules to develop an abstraction hierarchy from which multi-level rules can be extracted. The user is able to explore the knowledge at and across any of the levels of abstraction to provide a much richer picture of the knowledge and understanding of the domain.

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Author information

Authors and Affiliations

  1. Department of Computing, Centre for Language Technology, Division of Information and Communication Sciences, Macquarie University, Sydney, Australia

    Debbie Richards & Usama Malik

Authors
  1. Debbie Richards
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  2. Usama Malik
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Editor information

Editors and Affiliations

  1. University of Alberta, Canada

    Osmar R. Zaïane

  2. School of Computing and Mathematics, University of Western Sydney, Sydney, NSW, Australia

    Simeon J. Simoff

  3. LIFL-UMR CNRS 8022, Laboratoire d’Informatique Fondamentale de Lille, Université de Lille 1, France

    Chabane Djeraba

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Richards, D., Malik, U. (2003). Mining Propositional Knowledge Bases to Discover Multi-level Rules. In: Zaïane, O.R., Simoff, S.J., Djeraba, C. (eds) Mining Multimedia and Complex Data. PAKDD 2002. Lecture Notes in Computer Science(), vol 2797. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39666-6_13

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  • DOI: https://doi.org/10.1007/978-3-540-39666-6_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20305-6

  • Online ISBN: 978-3-540-39666-6

  • eBook Packages: Springer Book Archive

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