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Inform. Primen., 2013, Volume 7, Issue 1, Pages 90–93 (Mi ia248)  

This article is cited in 1 scientific paper (total in 1 paper)

Semantic vector spaces for different knowledge domains

Yu. I. Morozova

IPI RAN

Abstract: The paper focuses on the actual problems of studying semantics of linguistic units using the methods of corpus linguistics. It gives a review of distributional semantics which is a new area of linguistic research. The paper proposes an enhancement to the existing distributional models by switching from lexemes to word collocations. The paper describes the methodology used to build semantic vector spaces for different knowledge domains.

Keywords: distributional semantics; vector spaces; meaningful word combinations; collocations.

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Citation: Yu. I. Morozova, “Semantic vector spaces for different knowledge domains”, Inform. Primen., 7:1 (2013), 90–93

Citation in format AMSBIB
\Bibitem{Mor13}
\by Yu.~I.~Morozova
\paper Semantic vector spaces for~different knowledge domains
\jour Inform. Primen.
\yr 2013
\vol 7
\issue 1
\pages 90--93
\mathnet{http://mi.mathnet.ru/ia248}


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  • http://mi.mathnet.ru/eng/ia248
  • http://mi.mathnet.ru/eng/ia/v7/i1/p90

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    Citing articles on Google Scholar: Russian citations, English citations
    Related articles on Google Scholar: Russian articles, English articles

    This publication is cited in the following articles:
    1. I. V. Galina, E. B. Kozerenko, Yu. I. Morozova, N. V. Somin, M. M. Sharnin, “Assotsiativnye portrety predmetnoi oblasti — instrument avtomatizirovannogo postroeniya sistem big data dlya izvlecheniya znanii: teoriya, metodika, vizualizatsiya, vozmozhnoe primenenie”, Inform. i ee primen., 9:2 (2015), 92–110  mathnet  crossref  elib
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