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Using Web Mining for Discovering Spatial Patterns and Hot Spots for Spatial Generalization

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Foundations of Intelligent Systems (ISMIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7661))

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Abstract

In this paper we propose a novel approach to spatial data generalization, in which web user behavior information influences the generalization and mapping process. Our approach relies on combining usage information from web resources such as Wikipedia with search engines index statistics in order to determine an importance score for geographical objects that is used during map preparation.

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Author information

Authors and Affiliations

  1. Nicolaus Copernicus University of Torun, Gagarina 11, 87-100, Torun, Poland

    Jan Burdziej

  2. Institute of Computer Science, Faculty of Electronics and Information Technology, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Piotr Gawrysiak

Authors
  1. Jan Burdziej
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  2. Piotr Gawrysiak
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Editor information

Editors and Affiliations

  1. Hong Kong Baptist University, 224 Waterloo Road, Kowloon, Hong Kong

    Li Chen  & Jiming Liu  & 

  2. Institute for Software Technology, Graz University of Technology, Inffeldgasse 16b, 8010, Graz, Austria

    Alexander Felfernig

  3. University of North Carolina, Charlotte, NC 28223, USA and Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Zbigniew W. Raś

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© 2012 Springer-Verlag Berlin Heidelberg

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Burdziej, J., Gawrysiak, P. (2012). Using Web Mining for Discovering Spatial Patterns and Hot Spots for Spatial Generalization. In: Chen, L., Felfernig, A., Liu, J., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2012. Lecture Notes in Computer Science(), vol 7661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34624-8_21

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  • DOI: https://doi.org/10.1007/978-3-642-34624-8_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34623-1

  • Online ISBN: 978-3-642-34624-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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