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This chapter examines the methods of applying the word placement method based on the Word2vec model to the texts of the Uzbek language corpus. The Word2vec model has two types of variants: continuous bag of words (CBOW) and Skip Gram, and the chapter presents the architecture and algorithm of the Skip-Gram method. The Word2Vec method is a widely used artificial intelligence method in the field of natural language processing, serving to express words in the form of numerical vectors. The Word2Vec method identifies semantic and syntactic relationships between words based on a large corpus of the language. The visualization of the model formed by the Skip-Gram method for the corresponding Uzbek language corpus will be demonstrated.

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Processing of Uzbek Language Texts Using the Skip-Gram Method

  • 会议论文

  • 发表日期：

    2025年

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  • Elov Botir,
  • Ergasheva Guli,
  • Alaev Ruhillo,
  • Eshmuminov Askar,
  • Hamroyeva Shahlo,
  • Abdullayeva Oqila,
  • Khusainova Zilola

摘要

This chapter examines the methods of applying the word placement method based on the Word2vec model to the texts of the Uzbek language corpus. The Word2vec model has two types of variants: continuous bag of words (CBOW) and Skip Gram, and the chapter presents the architecture and algorithm of the Skip-Gram method. The Word2Vec method is a widely used artificial intelligence method in the field of natural language processing, serving to express words in the form of numerical vectors. The Word2Vec method identifies semantic and syntactic relationships between words based on a large corpus of the language. The visualization of the model formed by the Skip-Gram method for the corresponding Uzbek language corpus will be demonstrated.