Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser

This research is aimed at identifying the parts of speech for the Kazakh and Turkish languages in an information retrieval system. The proposed algorithms are based on machine learning techniques. In this paper, we consider the binary classification of words according to parts of speech. We decided...

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Autores principales:	Aigerim Yerimbetova, Madina Tussupova, Madina Sambetbayeva, Mussa Turdalyuly, Bakzhan Sakenov
Formato:	article
Lenguaje:	EN RU UK
Publicado:	PC Technology Center 2021
Materias:	natural language processing part-of-speech machine learning algorithms agglutinative language word2vec Technology (General) T1-995 Industry HD2321-4730.9
Acceso en línea:	https://doaj.org/article/56c34b6bc69a421498854528eacad6ff
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id	oai:doaj.org-article:56c34b6bc69a421498854528eacad6ff
record_format	dspace
spelling	oai:doaj.org-article:56c34b6bc69a421498854528eacad6ff2021-11-04T14:06:13ZGrammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser1729-37741729-406110.15587/1729-4061.2021.238743https://doaj.org/article/56c34b6bc69a421498854528eacad6ff2021-10-01T00:00:00Zhttp://journals.uran.ua/eejet/article/view/238743https://doaj.org/toc/1729-3774https://doaj.org/toc/1729-4061This research is aimed at identifying the parts of speech for the Kazakh and Turkish languages in an information retrieval system. The proposed algorithms are based on machine learning techniques. In this paper, we consider the binary classification of words according to parts of speech. We decided to take the most popular machine learning algorithms. In this paper, the following approaches and well-known machine learning algorithms are studied and considered. We defined 7 dictionaries and tagged 135 million words in Kazakh and 9 dictionaries and 50 million words in the Turkish language. The main problem considered in the paper is to create algorithms for the execution of dictionaries of the so-called Link Grammar Parser (LGP) system, in particular for the Kazakh and Turkish languages, using machine learning techniques. The focus of the research is on the review and comparison of machine learning algorithms and methods that have accomplished results on various natural language processing tasks such as grammatical categories determination. For the operation of the LGP system, a dictionary is created in which a connector for each word is indicated – the type of connection that can be created using this word. The authors considered methods of filling in LGP dictionaries using machine learning. The complexities of natural language processing, however, do not exclude the possibility of identifying narrower tasks that can already be solved algorithmically: for example, determining parts of speech or splitting texts into logical groups. However, some features of natural languages significantly reduce the effectiveness of these solutions. Thus, taking into account all word forms for each word in the Kazakh and Turkish languages increases the complexity of text processing by an order of magnitudeAigerim YerimbetovaMadina TussupovaMadina SambetbayevaMussa TurdalyulyBakzhan SakenovPC Technology Centerarticlenatural language processingpart-of-speechmachine learning algorithmsagglutinative languageword2vecTechnology (General)T1-995IndustryHD2321-4730.9ENRUUKEastern-European Journal of Enterprise Technologies, Vol 5, Iss 2 (113), Pp 55-65 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU UK
topic	natural language processing part-of-speech machine learning algorithms agglutinative language word2vec Technology (General) T1-995 Industry HD2321-4730.9
spellingShingle	natural language processing part-of-speech machine learning algorithms agglutinative language word2vec Technology (General) T1-995 Industry HD2321-4730.9 Aigerim Yerimbetova Madina Tussupova Madina Sambetbayeva Mussa Turdalyuly Bakzhan Sakenov Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
description	This research is aimed at identifying the parts of speech for the Kazakh and Turkish languages in an information retrieval system. The proposed algorithms are based on machine learning techniques. In this paper, we consider the binary classification of words according to parts of speech. We decided to take the most popular machine learning algorithms. In this paper, the following approaches and well-known machine learning algorithms are studied and considered. We defined 7 dictionaries and tagged 135 million words in Kazakh and 9 dictionaries and 50 million words in the Turkish language. The main problem considered in the paper is to create algorithms for the execution of dictionaries of the so-called Link Grammar Parser (LGP) system, in particular for the Kazakh and Turkish languages, using machine learning techniques. The focus of the research is on the review and comparison of machine learning algorithms and methods that have accomplished results on various natural language processing tasks such as grammatical categories determination. For the operation of the LGP system, a dictionary is created in which a connector for each word is indicated – the type of connection that can be created using this word. The authors considered methods of filling in LGP dictionaries using machine learning. The complexities of natural language processing, however, do not exclude the possibility of identifying narrower tasks that can already be solved algorithmically: for example, determining parts of speech or splitting texts into logical groups. However, some features of natural languages significantly reduce the effectiveness of these solutions. Thus, taking into account all word forms for each word in the Kazakh and Turkish languages increases the complexity of text processing by an order of magnitude
format	article
author	Aigerim Yerimbetova Madina Tussupova Madina Sambetbayeva Mussa Turdalyuly Bakzhan Sakenov
author_facet	Aigerim Yerimbetova Madina Tussupova Madina Sambetbayeva Mussa Turdalyuly Bakzhan Sakenov
author_sort	Aigerim Yerimbetova
title	Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
title_short	Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
title_full	Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
title_fullStr	Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
title_full_unstemmed	Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
title_sort	grammatical categories determination for turkish and kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser
publisher	PC Technology Center
publishDate	2021
url	https://doaj.org/article/56c34b6bc69a421498854528eacad6ff
work_keys_str_mv	AT aigerimyerimbetova grammaticalcategoriesdeterminationforturkishandkazakhlanguagesbasedonmachinelearningalgorithmsandfulfillingdictionariesoflinkgrammarparser AT madinatussupova grammaticalcategoriesdeterminationforturkishandkazakhlanguagesbasedonmachinelearningalgorithmsandfulfillingdictionariesoflinkgrammarparser AT madinasambetbayeva grammaticalcategoriesdeterminationforturkishandkazakhlanguagesbasedonmachinelearningalgorithmsandfulfillingdictionariesoflinkgrammarparser AT mussaturdalyuly grammaticalcategoriesdeterminationforturkishandkazakhlanguagesbasedonmachinelearningalgorithmsandfulfillingdictionariesoflinkgrammarparser AT bakzhansakenov grammaticalcategoriesdeterminationforturkishandkazakhlanguagesbasedonmachinelearningalgorithmsandfulfillingdictionariesoflinkgrammarparser
_version_	1718444839149764608

Grammatical categories determination for Turkish and Kazakh languages based on machine learning algorithms and fulfilling dictionaries of link grammar parser

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