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An Analysis of Linear Weight Updating Algorithms for Text Classification

  • Conference paper
Advances in Artificial Intelligence (SETN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3955))

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Abstract

This paper addresses the problem of text classification in high dimensionality spaces by applying linear weight updating classifiers that have been highly studied in the domain of machine learning. Our experimental results are based on the Winnow family of algorithms that are simple to implement and efficient in terms of computation time and storage requirements. We applied an exponential multiplication function to weight updates and we experimentally calculated the optimal values of the learning rate and the separating surface parameters. Our results are at the level of the best results that were reported on the family of linear algorithms and perform nearly as well as the top performing methodologies in the literature.

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Author information

Authors and Affiliations

  1. Institute for Language and Speech Processing, Artemidos 6 & Epidavrou, Athens, 15125, Greece

    Aggelos Gkiokas, Iason Demiros & Stelios Piperidis

  2. National Technical University of Athens, Greece

    Aggelos Gkiokas & Iason Demiros

Authors
  1. Aggelos Gkiokas
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  2. Iason Demiros
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  3. Stelios Piperidis
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Editor information

Editors and Affiliations

  1. Computer Science Department of University of Crete, Greece

    Grigoris Antoniou

  2. Institute of Computer Science, Foundation for Research & Technology – Hellas (FORTH), Vassilika Vouton, P.O. Box 1385, 71110, Heraklion, Greece

    George Potamias

  3. Institute of Informatics and Telecommunications, NCSR "Demokritos", 15310 A., Paraskevi Attikis, Greece

    Costas Spyropoulos

  4. Institute of Computer Science, FO.R.T.H., Vassilika Vouton, P.O. Box 1385, GR 71110, Heraklion, Greece

    Dimitris Plexousakis

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© 2006 Springer-Verlag Berlin Heidelberg

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Gkiokas, A., Demiros, I., Piperidis, S. (2006). An Analysis of Linear Weight Updating Algorithms for Text Classification. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_56

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  • DOI: https://doi.org/10.1007/11752912_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34117-8

  • Online ISBN: 978-3-540-34118-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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