IDENTIFYING SPAM MESSAGES FOR KAZAKH LANGUAGE USING HYBRID MACHINE LEARNING MODEL

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Date

2023

Journal Title

Journal ISSN

Volume Title

Publisher

СДУ хабаршысы - 2023

Abstract

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.

Description

Keywords

Spam classification, spam detection, spam filtering methods, machine learning, data preprocessing for Kazakh language, СДУ хабаршысы - 2023, №1

Citation

Bilakhanova A , A. Ydvrys , N. Sultanova / IDENTIFYING SPAM MESSAGES FOR KAZAKH LANGUAGE USING HYBRID MACHINE LEARNING MODEL / СДУ хабаршысы - 2023