Automatic processing methods of the kazakh language in intelligent information systems

Abstract

Automatic processing of the Kazakh language is an important part of modern information systems. This article reviews automatic processing methods used in intelligent information systems considering the morphological features of the Kazakh language. The limitations of traditional rule-based and statistical methods are compared with the effectiveness of deep learning models based on transformer architectures. Research results show that modern methods can accurately analyze text while considering the complexity of the Kazakh language. This work contributes to the development of intelligent systems in Kazakh.