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Local and Global Methods in Data Mining: Basic Techniques and Open Problems

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Automata, Languages and Programming (ICALP 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2380))

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Abstract

Data mining has in recent years emerged as an interesting area in the boundary between algorithms, probabilistic modeling, statistics, and databases. Data mining research can be divided into global approaches, which try to model the whole data, and local methods, which try to find useful patterns occurring in the data. We discuss briefly some simple local and global techniques, review two attempts at combining the approaches, and list open problems with an algorithmic flavor.

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Author information

Authors and Affiliations

  1. Department of Computer Science, HIIT Basic Research Unit, University of Helsinki, PO Box 26, FIN-00014, University of Helsinki, Finland

    Heikki Mannila

  2. Laboratory of Computer and Information Science, Helsinki University of Technology, PO Box 5400, FIN-02015, HUT, Finland

    Heikki Mannila

Authors
  1. Heikki Mannila
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Editor information

Editors and Affiliations

  1. Institute of Theoretical Computer Science, ETH Zentrum, ETH Zürich, 8092, Zürich, Switzerland

    Peter Widmayer  & Stephan Eidenbenz  & 

  2. Department of Languages and Sciences of the Computation E.T.S. de Ingeniería Informática, University of Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Francisco Triguero , Rafael Morales  & Ricardo Conejo ,  & 

  3. School of Cognitive and Computing Sciences, University of Sussex, Falmer, Brighton, BN1 9QN, UK

    Matthew Hennessy

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© 2002 Springer-Verlag Berlin Heidelberg

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Mannila, H. (2002). Local and Global Methods in Data Mining: Basic Techniques and Open Problems. In: Widmayer, P., Eidenbenz, S., Triguero, F., Morales, R., Conejo, R., Hennessy, M. (eds) Automata, Languages and Programming. ICALP 2002. Lecture Notes in Computer Science, vol 2380. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45465-9_6

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  • DOI: https://doi.org/10.1007/3-540-45465-9_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43864-9

  • Online ISBN: 978-3-540-45465-6

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