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A Genetic Programming Approach for Combining Structural and Citation-Based Evidence for Text Classification in Web Digital Libraries

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Soft Computing in Web Information Retrieval

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 197))

Summary

This paper investigates how citation-based information and structural content (e.g., title, abstract) can be combined to improve classification of text documents into predefined categories. We evaluate different measures of similarity, five derived from the citation structure of the collection, and three measures derived from the structural content, and determine how they can be fused to improve classification effectiveness. To discover the best fusion framework, we apply Genetic Programming (GP) techniques. Our empirical experiments using documents from the ACM digital library and the ACM classification scheme show that we can discover similarity functions that work better than any evidence in isolation and whose combined performance through a simple majority voting is comparable to that of Support Vector Machine classifiers.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA

    Baoping Zhang, Weiguo Fan, Yuxin Chen & Edward A. Fox

  2. Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil

    Marcos André Gonçalves & Marco Cristo

  3. Pável Calado, IST/INESC-ID, Lisbon, Portugal

    Pável Calado

Authors
  1. Baoping Zhang
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  2. Weiguo Fan
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  3. Yuxin Chen
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  4. Edward A. Fox
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  5. Marcos André Gonçalves
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  6. Marco Cristo
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  7. Pável Calado
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Editor information

Editors and Affiliations

  1. Department of Computer Science and A.I E.T.S.I. Informatica, University of Granada, C/Periodista Daniel, Saucedo Aranda s/n, Granada, Spain

    Enrique Herrera-Viedma

  2. Department of Informatics Systems and Communication (DISCo), Università degli Studi di Milano Bicocca, Via Bicocca degli Arcimboldi, 8 (Edificio U7), 20126, Milano, Itay

    Gabriella Pasi

  3. Department of Computer and Information Sciences, University of Strathclyde, Livingstone Tower, 26 Richmond Street, Glasgow, G1 1XH, Scotland, UK

    Fabio Crestani

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, B. et al. (2006). A Genetic Programming Approach for Combining Structural and Citation-Based Evidence for Text Classification in Web Digital Libraries. In: Herrera-Viedma, E., Pasi, G., Crestani, F. (eds) Soft Computing in Web Information Retrieval. Studies in Fuzziness and Soft Computing, vol 197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31590-X_4

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  • DOI: https://doi.org/10.1007/3-540-31590-X_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31588-9

  • Online ISBN: 978-3-540-31590-2

  • eBook Packages: EngineeringEngineering (R0)

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