Semantic Similarity Identification for Short Text Fragments

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dc.contributor.authorChuiko, Viktoriiaen
dc.contributor.authorKhairova, N. F.en
dc.date.accessioned2020-12-11T12:58:01Z
dc.date.available2020-12-11T12:58:01Z
dc.date.issued2019
dc.description.abstractThe paper contains review of the existing methods for semantic similarity identification, such as methods based on the distance between concepts and methods based on lexical intersection. We proposed a method for measuring the semantic similarity of short text fragment, i.e. two sentences. Also, we created corpus of mass-media text. It contains articles of Kharkiv news, that were sorted by their source and date. Then we annotated texts. We defined semantic similarity of sentences manually. In this way, we created learning corpus for our future system.en
dc.identifier.citationChuiko V. Semantic Similarity Identification for Short Text Fragments [Electronic resource] / V. Chuiko, N. Khairova // Computational linguistics and intelligent systems (COLINS 2019) : proc. of the 3d Intern. Conf., April 18-19, 2019. Vol. 2: Workshop / ed.: V. Lytvyn [et al.]. – Electron. text data. – Lviv, 2019. – P. 57-59. – URL: http://colins.in.ua/wp-content/uploads/2019/12/colins_2019_57-59.pdf, free (accessed 11.12.2020).en
dc.identifier.orcidhttps://orcid.org/0000-0002-4393-3260
dc.identifier.orcidhttps://orcid.org/0000-0002-9826-0286
dc.identifier.urihttps://repository.kpi.kharkov.ua/handle/KhPI-Press/49772
dc.language.isoen
dc.subjectsemantic similarityen
dc.subjectshort text fragmentsen
dc.subjectorpus of mass-media texten
dc.subjectautomatic identificationen
dc.titleSemantic Similarity Identification for Short Text Fragmentsen
dc.typeThesisen

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Кафедра "Інтелектуальні комп'ютерні системи"