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A Method for Aggregating Partitions, Applications in K.D.D.

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Advances in Knowledge Discovery and Data Mining (PAKDD 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2637))

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Abstract

K.D.D. (Knowledge Discovery in Databases) methods and methodologies nearly all imply the retrieval of one or several structures of a data set. In practice, using those methods may give rise to a bunch of problems (excessive computing time, parameters settings,...). We show in this paper that some of these problems can be solved via the construction of a global structure starting from a set of sub-structures. We thus propose a method for aggregating a set of partial structures into a global one and then present how this method can be used for solving several traditional practical problems of K.D.D....

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Author information

Authors and Affiliations

  1. LABORATOIRE ERIC (Equipe de Recherche en Ingénierie des Connaissances), Université Lumière — Lyon2, Bâtiment L, 5 avenue Pierre, Mendès-France, 69 676, BRON cedex, FRANCE

    Pierre-Emmanuel Jouve & Nicolas Nicoloyannis

Authors
  1. Pierre-Emmanuel Jouve
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  2. Nicolas Nicoloyannis
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Editor information

Editors and Affiliations

  1. Computer Science Department, Korea Advanced Institute of Science and Technology, 373-1 Koo-Sung Dong, Yoo-Sung Ku, Daejeon, 305-701, Korea

    Kyu-Young Whang

  2. Department of Statistics, Seoul National University, Sillimdong Kwanakgu, Seoul, 151-742, Korea

    Jongwoo Jeon

  3. School of Electrical Engineering and Computer Science, Seoul National University, Kwanak P.O. Box 34, Seoul, 151-742, Korea

    Kyuseok Shim

  4. Department of Computer Science and Engineering, University of Minnesota, 200 Union St SE, Minneapolis, MN, 55455, USA

    Jaideep Srivastava

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© 2003 Springer-Verlag Berlin Heidelberg

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Jouve, PE., Nicoloyannis, N. (2003). A Method for Aggregating Partitions, Applications in K.D.D.. In: Whang, KY., Jeon, J., Shim, K., Srivastava, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2003. Lecture Notes in Computer Science(), vol 2637. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36175-8_41

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  • DOI: https://doi.org/10.1007/3-540-36175-8_41

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-04760-5

  • Online ISBN: 978-3-540-36175-6

  • eBook Packages: Springer Book Archive

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