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LTC 2011: Human Language Technology Challenges for Computer Science and Linguistics pp 396–407Cite as

Classification-Based Extension of Wordnets from Heterogeneous Resources

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8387))

Abstract

This paper presents an automatic and language-independent approach for word net extension by reusing existing freely available bilingual resources, such as machine-readable dictionaries and on-line encyclopaedias. The approach is applied to Slovene and French. The words from the bilingual resources are assigned one or several synset ids based on a classifier that relies on a set of features, the most important one of which is distributional similarity. Automatic, manual and task-based evaluations show good results in terms of both coverage and quality.

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Notes

  1. 1.

    http://presis.amebis.si/prevajanje/ [3.6.2011].

  2. 2.

    http://translate.google.com/ [3.6.2011].

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Author information

Authors and Affiliations

  1. Alpage, INRIA and Université Paris-Diderot, rue Albert Einstein, 75013, Paris, France

    Benoît Sagot

  2. Department of Translation, University of Ljubljana, Aškerčeva 2, SI – 1000, Ljubljana, Slovenia

    Darja Fišer

Authors
  1. Benoît Sagot
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  2. Darja Fišer
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Corresponding author

Correspondence to Benoît Sagot .

Editor information

Editors and Affiliations

  1. Adam Mickiewicz University, Poznań, Poland

    Zygmunt Vetulani

  2. IMMI-CNRS, Orsay, France

    Joseph Mariani

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Sagot, B., Fišer, D. (2014). Classification-Based Extension of Wordnets from Heterogeneous Resources. In: Vetulani, Z., Mariani, J. (eds) Human Language Technology Challenges for Computer Science and Linguistics. LTC 2011. Lecture Notes in Computer Science(), vol 8387. Springer, Cham. https://doi.org/10.1007/978-3-319-08958-4_32

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  • DOI: https://doi.org/10.1007/978-3-319-08958-4_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08957-7

  • Online ISBN: 978-3-319-08958-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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