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Intelligent Web Mining

  • Chapter
Intelligent Exploration of the Web

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 111))

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Abstract

Explosive growth in size and usage of the World Wide Web has made it Necessary for Web site administrators to track and analyze the navigation patterns of Web site visitors. However, data mining techniques are not easily applicable to Web data due to problems both related with the technology underlying the Web and the lack of standards in the design and implementation of Web pages. Information collected by Web servers and kept in the server log is the main source of data for analyzing user navigation patterns.

Once logs have been preprocessed and sessions have been obtained there are several kinds of access pattern mining that can be performed depending on the needs of the analyst. It is important to mention that most efforts have relied on relatively simple techniques which can be inadequate for real user profile data since noise in the data has to be firstly tacked. Thus, there is a need for robust methods that integrates different intelligent techniques that are free of any assumptions about the noise contamination rate.

In this paper, the problem of mining behavior patterns on the Web is studied in detail and different approaches to solve the problem are analyzed. An algorithm is given to calculate frequent access patterns. This algorithm is based on a model structure that has been called WPC-Tree that stores in each node relevant information about pages that make it possible to apply data mining techniques to obtain useful patterns.

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Author information

Authors and Affiliations

  1. DLSIIS Facultad de Informática, U.P.M., Madrid, Spain

    Ernestina Menasalvas

  2. Departamento de Informática, Universidad Carlos III, Madrid, Spain

    Oscar Marbán

  3. Universidad del Valle, Cali., Colombia

    Socorro Millán

  4. DATSI Facultad de Informática, U.P.M., Madrid, Spain

    Jose M. Peña

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  1. Ernestina Menasalvas
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  2. Oscar Marbán
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  3. Socorro Millán
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  4. Jose M. Peña
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, Technical University of Lodz, ul. Sterlinga 16/18, 90-217, Lodz, Poland

    Piotr S. Szczepaniak

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Piotr S. Szczepaniak  & Janusz Kacprzyk  & 

  3. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660, Madrid, Spain

    Javier Segovia

  4. Computer Science Division, Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

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© 2003 Springer-Verlag Berlin Heidelberg

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Menasalvas, E., Marbán, O., Millán, S., Peña, J.M. (2003). Intelligent Web Mining. In: Szczepaniak, P.S., Segovia, J., Kacprzyk, J., Zadeh, L.A. (eds) Intelligent Exploration of the Web. Studies in Fuzziness and Soft Computing, vol 111. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1772-0_22

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  • DOI: https://doi.org/10.1007/978-3-7908-1772-0_22

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2519-0

  • Online ISBN: 978-3-7908-1772-0

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