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Named Entities as New Features for Czech Document Classification

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Computational Linguistics and Intelligent Text Processing (CICLing 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8404))

Abstract

This paper is focused on automatic document classification. The results will be used to develop a real application for the Czech News Agency. The main goal of this work is to propose new features based on the Named Entities (NEs) for this task. Five different approaches to employ NEs are suggested and evaluated on a Czech newspaper corpus. We show that these features do not improve significantly the score over the baseline word-based features. The classification error rate improvement is only about 0.42% when the best approach is used.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science & Engineering, and NTIS - New Technologies for the Information Society Faculty of Applied Sciences, University of West Bohemia, Plzeň, Czech Republic

    Pavel Král

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  1. Pavel Král
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Editor information

Editors and Affiliations

  1. Center for Computing Research, National Polytechnic Institute, Av. Juan Dios Bátiz, Col. Nueva Industrial Vallejo, 07738, Mexico D.F, Mexico

    Alexander Gelbukh

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Král, P. (2014). Named Entities as New Features for Czech Document Classification. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54903-8_35

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  • DOI: https://doi.org/10.1007/978-3-642-54903-8_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54902-1

  • Online ISBN: 978-3-642-54903-8

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