Abstract
The classification of questions plays a key role in the system of the question-answer system, helping in the search or construction of accurate answers and thereby improving the quality of the answers provided. The following approaches are usually used to classify questions: rule-based, machine learning, and hybrid. The Kazakh language is an agglutinative language with complex morphological and syntactic involvement of polysynthetism, and therefore it is difficult to conduct machine learning research. This article presents a study on the classification of questions using rules. The question processing module helps you assign appropriate categories to questions and identify keywords from the provided input question. A prototype program was developed based on the proposed method, and an experiment was conducted involving 200 legislative questions collected from government websites such as egov.kz, adilet.kz and zan.kz . Using these question templates, the questions were categorized into specific categories. In this article, we have proposed a compact and effective method for classifying questions. The results of the experiment show that even with a small set of question categories, we can classify them with a more satisfactory and improved result.