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The Task of Generating Text Based on a Semantic Approach for a Low-Resource Kazakh Language

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2023)

Abstract

In this article, the authors consider the problem of text generation for low- resource languages, using the Kazakh language as an example, based on semantic analysis. Machine learning method is used in the generation of text documents and sources in the Kazakh language. First, semantic analysisis performed, the number of words in the given text, the number of stop words, the number of symbols, etc. Then the TF-IDF algorithm is used to find the semantically important words of the text. Annotation of the given text by means of semantic analysis. And at the end, generation of text with advanced semantic analysis. A corpus for the Kazakh language was prepared for experiments and research. GPT-3 and NLG are used in the process of generation. Generation by means of semantic analysis of the text gives us some great opportunities. The Recurrent Neural Network (RNN) method is used during generation.Generation gives us a lot of opportunities, including not spending time on unnecessary information. It will provide an article or short text related to the keywords you searched for. The description of the developed approach and practical results of experiments are presented.

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Acknowledgments

This research was performed and financed by the grant Project IRN AP 09259556 of Ministry of Science and Higher Education of the Republic of Kazakhstan.

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Correspondence to Diana Rakhimova .

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Rakhimova, D., Abilay, S., Kuralay, A. (2023). The Task of Generating Text Based on a Semantic Approach for a Low-Resource Kazakh Language. In: Nguyen, N.T., et al. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2023. Communications in Computer and Information Science, vol 1863. Springer, Cham. https://doi.org/10.1007/978-3-031-42430-4_48

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  • DOI: https://doi.org/10.1007/978-3-031-42430-4_48

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  • Online ISBN: 978-3-031-42430-4

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