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Development of Morphological Segmentation for the Kyrgyz Language on Complete Set of Endings

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Intelligent Information and Database Systems (ACIIDS 2021)

Abstract

The problem of word segmentation of source texts in the training of neural network models is one of the actual problems of natural language processing. A new model of the morphology of the Kyrgyz language based on a complete set of endings (CSE) is developed. Based on the developed CSE-model of the morphology of the Kyrgyz language, a computational data model, algorithm and a program for morphological segmentation are developed. Experiments on morphological segmentation of Kyrgyz language texts showed 82% accuracy of text segmentation by the proposed method.

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Notes

  1. 1.

    https://github.com/NLP-KazNU.

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Toleush, A., Israilova, N., Tukeyev, U. (2021). Development of Morphological Segmentation for the Kyrgyz Language on Complete Set of Endings. In: Nguyen, N.T., Chittayasothorn, S., Niyato, D., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2021. Lecture Notes in Computer Science(), vol 12672. Springer, Cham. https://doi.org/10.1007/978-3-030-73280-6_26

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  • DOI: https://doi.org/10.1007/978-3-030-73280-6_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73279-0

  • Online ISBN: 978-3-030-73280-6

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