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The Variable Precision Rough Set Inductive Logic Programming Model and Future Test Cases in Web Usage Mining

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Rough Set Theory and Granular Computing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 125))

Abstract

The Variable Precision Rough Set Inductive Logic Programming model (VPRSILP model) is the extension of the Variable Precision Rough Set (VPRS) model to Inductive Logic Programming (ILP). The generic Rough Set Inductive Logic Programming (gRS-ILP) model provides a framework for ILP when the setting is imprecise and any induced logic program will not be able to distinguish between certain positive and negative examples. The gRS-ILP model is extended to the VPRSILP model by including features of the VPRS model. The VPRSILP model is further extended in this paper to include future test cases. This model is applied to Web usage mining and an illustrative experiment is presented.

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Author information

Authors and Affiliations

  1. Anna University, Chennai, 600 025, India

    V. Uma Maheswari, Arul Siromoney & K. M. Mehata

Authors
  1. V. Uma Maheswari
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  2. Arul Siromoney
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  3. K. M. Mehata
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Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Osaka University, Yamada-Oka, Suita 2-1, 565-0871, Osaka, Japan

    Masahiro Inuiguchi

  2. Shimane Medical University, Enya-Cho 89-1, 693-8501, Izumo, Shimane-ken, Japan

    Shoji Hirano  & Shusaku Tsumoto  & 

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© 2003 Springer-Verlag Berlin Heidelberg

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Maheswari, V.U., Siromoney, A., Mehata, K.M. (2003). The Variable Precision Rough Set Inductive Logic Programming Model and Future Test Cases in Web Usage Mining. In: Inuiguchi, M., Hirano, S., Tsumoto, S. (eds) Rough Set Theory and Granular Computing. Studies in Fuzziness and Soft Computing, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36473-3_18

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  • DOI: https://doi.org/10.1007/978-3-540-36473-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05614-7

  • Online ISBN: 978-3-540-36473-3

  • eBook Packages: Springer Book Archive

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