Computational linguistics and intelligent systems. – 2019 р.

Permanent URI for this collectionhttps://ena.lpnu.ua/handle/ntb/45481

Періодичне видання за матеріалами конференції

This volume represents the proceedings of the Workshop Conference, with Posters and Demonstrations track, of the 3rd International Conference on Computational Linguistics and Intelligent Systems, held in Kharkiv, Ukraine, in April 2019. It comprises 13 contributed papers that were carefully peer-reviewed and selected from 27 submissions. The volume opens with the abstracts of the keynote talks. The rest of the collection is organized in two parts. Parts II contain the contributions to the Main COLINS Conference tracks, structured in two topical sections: (I) Computational Linguistics; (II) Intelligent Systems.

Computational Linguistics and Intelligent Systems. – Lviv : Lviv Politechnic Publishing House, 2019. – Volume 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18–19, 2019. – 78 p.

Computational Linguistics and Intelligent Systems

Зміст (том 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019)


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Content (Vol. 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019)


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    Machine learning text classification model with NLP approach
    (Lviv Politechnic Publishing House, 2019-04-18) Razno, Maria; National Technical University "Kharkiv Polytechnic Institute"
    This article describes the relevance of the word processing task that is written in human language by the methods of Machine Learning and NLP approach, that can be used on Python programming language. It also portrays the concept of Machine Learning, its main varieties and the most popular Pythonpackages and libraries for working with text data using Machine Learning methods. The concept of NLP and the most popular python packages are also presented in the article. The machine learning classification model algorithm based on the text processing is introduced in the article. It shows how to use classification machine learning and NLP methods in practice.
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    Identify of the substantive, attribute, and verb collocations in russian text
    (Lviv Politechnic Publishing House, 2019-04-18) Lytvynenko, Julia; National Technical University «Kharkiv Polytechnic Institute»
    This article describes methods and existing libraries for POS-tagging and collocations extraction, using NLP technologies, processing natural language text in the Python programming language. In addition, it describes one of the possible methods for the selection of collocations for a given pattern.