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Semantic and Syntactic Model of Natural Language Based on Tensor Factorization

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Natural Language Processing and Information Systems (NLDB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8455))

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Abstract

A method of developing a structural model of natural language syntax and semantics is proposed. Factorization of lexical combinability arrays obtained from text corpora generates linguistic databases that used for natural language semantic and syntactic analyses.

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References

  1. Van de Cruys, T.: A Non-Negative Tensor Factorization Model for Selectional Preference Induction. Journal of Natural Language Engineering 16(4), 417–437 (2010)

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  2. Van de Cruys, T., Rimell, L., Poibeau, T., Korhonen, A.: Multi-Way Tensor Factorization for Unsupervised Lexical Acquisition. In: Proceedings of COLING 2012, pp. 2703–2720 (2012)

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  3. Anisimov, A.V.: Control Space of Syntactic Structures of Natural Language. Cybernetics and System Analysis 3, 11–17 (1990)

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Author information

Authors and Affiliations

  1. Faculty of Cybernetics, Taras Shevchenko National University of Kyiv, Ukraine

    Anatoly Anisimov, Oleksandr Marchenko, Volodymyr Taranukha & Taras Vozniuk

Authors
  1. Anatoly Anisimov
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  2. Oleksandr Marchenko
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  3. Volodymyr Taranukha
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  4. Taras Vozniuk
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Editor information

Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Computer Science,, 2 rue Conté, 75003, Paris, France

    Elisabeth Métais

  2. Cirad, TETIS, 500 rue J.F. Breton, 34093, Montpellier Cedex 5, France

    Mathieu Roche

  3. Irstea, TETIS, 500 rue J.F. Breton, 34093, Montpellier Cedex 5, France

    Maguelonne Teisseire

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© 2014 Springer International Publishing Switzerland

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Anisimov, A., Marchenko, O., Taranukha, V., Vozniuk, T. (2014). Semantic and Syntactic Model of Natural Language Based on Tensor Factorization. In: Métais, E., Roche, M., Teisseire, M. (eds) Natural Language Processing and Information Systems. NLDB 2014. Lecture Notes in Computer Science, vol 8455. Springer, Cham. https://doi.org/10.1007/978-3-319-07983-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-07983-7_7

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07982-0

  • Online ISBN: 978-3-319-07983-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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