Browsing by Author "Bilakhanova A."

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    IDENTIFYING SPAM MESSAGES FOR KAZAKH LANGUAGE USING HYBRID MACHINE LEARNING MODEL
    (СДУ хабаршысы - 2023, 2023) Bilakhanova A.; Ydvrys A. ; Sultanova N.
    Abstract. This paper describes a spam detection system for Kazakh Language using Hybrid Machine Learning Model. The lack of spam detection systems in the Kazakh language calls for the need of a proposed system that can identify unwanted messages. The system integrates multiple Machine Learning algorithms to accurately classify spam and non-spam messages. The performance of the system is evaluated using metrics such as accuracy, precision, recall, and Fl-score. Results show that the proposed solution outperforms existing spam detection techniques in terms of detecting spam with a low false positive rate and high accuracy. The findings of this research contribute to the development of effective spam detection systems for the Kazakh language and provide insights for future work in this field.
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    KAZAKH LANGUAGE-BASED QUESTION ANSWERING SYSTEM USING DEEP LEARNING APPROACH
    (СДУ хабаршысы - 2023, 2023) Bilakhanova A. ; Ydyrvs A.; Sultanova N.
    Abstract. Deep learning advances have resulted in considerable gains in a variety of natural language processing applications, including questionanswering (QA) systems. QA systems are intended to retrieve data from big datasets and respond to user queries using natural language. Deep learning-based techniques have yielded encouraging results in the development of QA systems capable of providing consistent answers to a wide range of inquiries. This research presents a deep learning-based Kazakh language-based QA system. A pre-processing module is also included in the proposed system to improve the quality of the input text and the accuracy of the final output. The results reveal that the system has a high level of accuracy. This study promotes to the advancement of question-answering technology and contributes to the development of natural language processing tools in the Kazakh language.