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Towards Automatic Classification of Wikipedia Content

  • Conference paper
Intelligent Data Engineering and Automated Learning – IDEAL 2010 (IDEAL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6283))

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Abstract

Wikipedia – the Free Encyclopedia encounters the problem of proper classification of new articles everyday. The process of assignment of articles to categories is performed manually and it is a time consuming task. It requires knowledge about Wikipedia structure, which is beyond typical editor competence, which leads to human-caused mistakes – omitting or wrong assignments of articles to categories. The article presents application of SVM classifier for automatic classification of documents from The Free Encyclopedia. The classifier application has been tested while using two text representations: inter-documents connections (hyperlinks) and word content. The results of the performed experiments evaluated on hand crafted data show that the Wikipedia classification process can be partially automated. The proposed approach can be used for building a decision support system which suggests editors the best categories that fit new content entered to Wikipedia.

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Author information

Authors and Affiliations

  1. Gdańsk University of Technology, Narutowicza 11/12, 80-952, Gdańsk, Poland

    Julian Szymański

Authors
  1. Julian Szymański
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Editor information

Editors and Affiliations

  1. School of Computing, University of the West of Scotland, PA1 2BE, Paisley, UK

    Colin Fyfe

  2. University of Birmingham, B15 2TT, Birmingham, UK

    Peter Tino

  3. University of Ulster, Coleraine, UK

    Darryl Charles

  4. Universidad de Burgos, Burgos, Spain

    Cesar Garcia-Osorio

  5. School of Electrical and Electronic Engineering, University of Manchester, Sackville Street Building, Sackville Street, M60 1QD, Manchester, UK

    Hujun Yin

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© 2010 Springer-Verlag Berlin Heidelberg

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Szymański, J. (2010). Towards Automatic Classification of Wikipedia Content. In: Fyfe, C., Tino, P., Charles, D., Garcia-Osorio, C., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2010. IDEAL 2010. Lecture Notes in Computer Science, vol 6283. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15381-5_13

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  • DOI: https://doi.org/10.1007/978-3-642-15381-5_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15380-8

  • Online ISBN: 978-3-642-15381-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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