A distributional semantics model for idiom detection the case of english and Russian

Jing Peng, Katsiaryna Aharodnik, Anna Feldman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper describes experiments in English and Russian automatic idiom detection. Our algorithm is based on the idea that literal and idiomatic expressions appear in different contexts. This difference is captured by our distributional semantics model. We evaluate our model on both languages and compare its results. We show that our model is language-independent. We also describe a new annotated resource we created for our experiments.

Original languageEnglish
Title of host publicationICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence
EditorsJaap van den Herik, Ana Paula Rocha
PublisherSciTePress
Pages675-682
Number of pages8
ISBN (Electronic)9789897582752
StatePublished - 1 Jan 2018
Event10th International Conference on Agents and Artificial Intelligence, ICAART 2018 - Funchal, Madeira, Portugal
Duration: 16 Jan 201818 Jan 2018

Publication series

NameICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence
Volume2

Other

Other10th International Conference on Agents and Artificial Intelligence, ICAART 2018
CountryPortugal
CityFunchal, Madeira
Period16/01/1818/01/18

Keywords

  • Corpus Annotation
  • Distributional Semantics
  • English
  • Idiom Recognition
  • Russian.

Fingerprint Dive into the research topics of 'A distributional semantics model for idiom detection the case of english and Russian'. Together they form a unique fingerprint.

  • Cite this

    Peng, J., Aharodnik, K., & Feldman, A. (2018). A distributional semantics model for idiom detection the case of english and Russian. In J. van den Herik, & A. P. Rocha (Eds.), ICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence (pp. 675-682). (ICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence; Vol. 2). SciTePress.