Using a Distributional Semantic Model for Collocation Identification

dc.contributor.authorMosinyan, Anna
dc.contributor.authorPetrasova, Svitlana
dc.date.accessioned2024-02-15T18:34:28Z
dc.date.available2024-02-15T18:34:28Z
dc.date.issued2020
dc.description.abstractThis paper proposes the approach to automatic collocation identification using both the distributional semantic model and POS-tagging. The authors suggest calculating PMI to obtain a sequence of collocations from the designed corpus of research abstracts. Then POS-tagging is applied to classify collocations extracted from the text corpus.
dc.identifier.citationMosinyan A. Using a Distributional Semantic Model for Collocation Identification [Electronic resource] / A. Mosinyan, S. Petrasova // Computational Linguistics and Intelligent Systems (COLINS 2020) : proc. of the 4th Intern. Conf., April 23-24, 2020. Vol. 2. – Electronic text data. – Lviv, 2020. – P. 236-237. – Access mode: https://colins.in.ua/wp-content/uploads/2020/06/preface_colins_volume2_2020_part6.pdf, free (date of the application 15.02.2024.).
dc.identifier.urihttps://repository.kpi.kharkov.ua/handle/KhPI-Press/74150
dc.language.isoen
dc.subjectdistributional semantics
dc.subjectPOS-tagging
dc.subjectcollocation
dc.subjecttext corpus
dc.subjectresearch abstracts
dc.titleUsing a Distributional Semantic Model for Collocation Identification
dc.typeArticle

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