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How Can Computer Science Contribute to Knowledge Discovery

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SOFSEM 2001: Theory and Practice of Informatics (SOFSEM 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2234))

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Abstract

Knowledge discovery, that is, to analyze a given massive data set and derive or discover some knowledge from it, has been becoming a quite important subject in several fields including computer science. Good softwares have been demanded for various knowledge discovery tasks. For such softwares, we often need to develop efficient algorithms for handling huge data sets. Random sampling is one of the important algorithmic methods for processing huge data sets. In this paper, we explain some random sampling techniques for speeding up learning algorithms and making them applicable to large data sets [15], [16], [4], [3]. We also show some algorithms obtained by using these techniques.

A part of this work is supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Scientific Research on Priority Areas (Discovery Science), 19982001.

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Author information

Authors and Affiliations

  1. Dept. of Mathematical and Computing Sciences, Tokyo Institute of Technology, Japan

    Osamu Watanabe

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  1. Osamu Watanabe
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Editors and Affiliations

  1. Institute of Computer Science, University of Wroclaw, Przesmyckiego 20, 51-151, Wroclaw, Poland

    Leszek Pacholski

  2. Fac. of Mathematics, Physics, and Informatics, Inst. of Informatics, Comenius Univ., Mlynská dolina, 84248, Bratislava, Slovakia

    Peter Ružička

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Watanabe, O. (2001). How Can Computer Science Contribute to Knowledge Discovery. In: Pacholski, L., Ružička, P. (eds) SOFSEM 2001: Theory and Practice of Informatics. SOFSEM 2001. Lecture Notes in Computer Science, vol 2234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45627-9_11

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  • DOI: https://doi.org/10.1007/3-540-45627-9_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42912-8

  • Online ISBN: 978-3-540-45627-8

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