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Gathering Information About Word Similarity from Neighbor Sentences

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Text, Speech, and Dialogue (TSD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9924))

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Abstract

In this paper we present the first results of detecting word semantic similarity on the Russian translations of Miller-Charles and Rubenstein-Goodenough sets prepared for the first Russian word semantic evaluation Russe-2015. The experiments were carried out on three text collections: Russian Wikipedia, a news collection, and their united collection. We found that the best results in detection of lexical paradigmatic relations are achieved using the combination of word2vec with the new type of features based on word co-occurrences in neighbor sentences.

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Notes

  1. 1.

    http://russe.nlpub.ru/.

  2. 2.

    https://code.google.com/archive/p/word2vec/.

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Acknowledgments

This work was partially supported by Russian Foundation for Basic Research, grant N14-07-00383.

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Authors and Affiliations

  1. Research Computing Center of Lomonosov Moscow State University, Moscow, Russia

    Natalia Loukachevitch & Aleksei Alekseev

Authors
  1. Natalia Loukachevitch
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  2. Aleksei Alekseev
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Corresponding author

Correspondence to Natalia Loukachevitch .

Editor information

Editors and Affiliations

  1. Masaryk University , Brno, Czech Republic

    Petr Sojka

  2. Masaryk University , Brno, Czech Republic

    Aleš Horák

  3. Masaryk University , Brno, Czech Republic

    Ivan Kopeček

  4. Masaryk University , Brno, Czech Republic

    Karel Pala

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Loukachevitch, N., Alekseev, A. (2016). Gathering Information About Word Similarity from Neighbor Sentences. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2016. Lecture Notes in Computer Science(), vol 9924. Springer, Cham. https://doi.org/10.1007/978-3-319-45510-5_16

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  • DOI: https://doi.org/10.1007/978-3-319-45510-5_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45509-9

  • Online ISBN: 978-3-319-45510-5

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