Kazakh language, question-answering system, naturallanguage processing, deep learning approach, accuracy

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.