Semantic Similarity Identification for Short Text Fragments
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Дата
2019
Автори
DOI
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Анотація
The 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.
Опис
Ключові слова
semantic similarity, short text fragments, orpus of mass-media text, automatic identification
Бібліографічний опис
Chuiko 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).