IDENTIFYING SPAM MESSAGES FOR KAZAKH LANGUAGE USING HYBRID MACHINE LEARNING MODEL

Simple item page
dc.contributor.authorBilakhanova A.
dc.contributor.author Ydvrys A.
dc.contributor.authorSultanova N.
dc.date.accessioned2024-01-04T11:32:08Z
dc.date.available2024-01-04T11:32:08Z
dc.date.issued2023
dc.description.abstractAbstract. 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.
dc.identifier.citationBilakhanova A , A. Ydvrys , N. Sultanova / IDENTIFYING SPAM MESSAGES FOR KAZAKH LANGUAGE USING HYBRID MACHINE LEARNING MODEL / СДУ хабаршысы - 2023
dc.identifier.issn2709-2631
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/1099
dc.language.isoen
dc.publisherСДУ хабаршысы - 2023
dc.subjectSpam classification
dc.subjectspam detection
dc.subjectspam filtering methods
dc.subjectmachine learning
dc.subjectdata preprocessing for Kazakh language
dc.subjectСДУ хабаршысы - 2023
dc.subject№1
dc.titleIDENTIFYING SPAM MESSAGES FOR KAZAKH LANGUAGE USING HYBRID MACHINE LEARNING MODEL
dc.typeArticle

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
2023.1 жаратылыстану-139-147.pdf
Size:
4.33 MB
Format:
Adobe Portable Document Format
Download

Collections

3. Articles and Papers