This research is aimed at identifying the parts of speech for the Kazakh and Turkish languages in an information retrieval system. The proposed algorithms are based on machine learning techniques. In this paper, we consider the binary classification of words according to parts of speech. We decided to take the most popular machine learning algorithms. In this paper, the following approaches and well-known machine learning algorithms are studied and considered. We defined 7 dictionaries and tagged 135 million words in Kazakh and 9 dictionaries and 50 million words in the Turkish language. The main problem considered in the paper is to create algorithms for the execution of dictionaries of the so-called Link Grammar Parser (LGP) system, in particular for the Kazakh and Turkish languages, using machine learning techniques. The focus of the research is on the review and comparison of machine learning algorithms and methods that have accomplished results on various natural language processing tasks such as grammatical categories determination. For the operation of the LGP system, a dictionary is created in which a connector for each word is indicated - the type of connection that can be created using this word. The authors considered methods of filling in LGP dictionaries using machine learning. The complexities of natural language processing, however, do not exclude the possibility of identifying narrower tasks that can already be solved algorithmically: for example, determining parts of speech or splitting texts into logical groups. However, some features of natural languages significantly reduce the effectiveness of these solutions. Thus, taking into account all word forms for each word in the Kazakh and Turkish languages increases the complexity of text processing by an order of magnitude.

Distributed information systems that support scientific and educational activities can work with various information systems. The main goal of creating a distributed information system supporting scientific and educational activities is to accelerate the pace and improve the quality of information exchange in the scientific environment. The paper considers technological methods for constructing models of information systems designed to support scientific and educational activities. The model under consideration is that the developed model of an information system for working with scientific materials should solve the problems of long-term storage of information, organizing data search by attributes, accumulating and replacing metadata. Based on the analysis of typical scenarios of information servers, the tasks that should be solved when organizing an access control system for distributed information resources are formulated. Within the framework of this technology, three access control models are discussed, which differ in the degree of integration of information server functions with the Z39.50 technologies. The creation and support of distributed information systems and electronic libraries that integrate heterogeneous information resources and operate in various software and hardware environments require special approaches to managing these systems. If the resources or data themselves can be managed locally, even for distributed information systems, then the task of managing access to distributed resources cannot be solved within the framework of local administration. The justification of the last thesis can be seen when considering typical scenarios of the information server, which we will describe below.

The paper deals with general issues of organizing access to electronic documents in the framework of scientific and educational activities. Large volumes of already existing information, its continuous growth, the heterogeneous nature of storage and distribution, the lack of a unified way of working with it create many difficulties when using it. Awareness of these difficulties, qualitative changes in the field of information technology and telecommunications have led to the need to solve the problem of finding new approaches to the creation of repositories of information resources, their structure, and the development of tools necessary for users. Currently, such approaches are called "digital" or "electronic" libraries. According to the preliminary concept, an intelligent scientific and educational Internet resource will be an information system accessible via the Internet, providing systematization and integration of scientific knowledge, data, and information resources into a single information space, meaningful and effective access to them, as well as support for their use in solving various scientific and educational tasks. Another problem of the organization of effective information support for scientific and educational activities is that, due to its diversity and multidimensional nature, scientific and educational information resources are dispersed on remote pages of many sites and in distributed electronic libraries and archives. To solve this problem, it is necessary to solve the problem of bringing such resources related to one area of knowledge into a single information space, and also, no less important, to support their logical integrity. Without solving these two related tasks, it is impossible to solve the main task - to provide all participants of scientific and educational activities with meaningful access to integrated information resources and means of their analysis. The support of information systems in the field of scientific and educational activities is relevant, since the need for information always exists. In order to satisfy this need, it is necessary to organize access to various resources.

With the daily increase in document flow, as well as the transition to paperless document management around the world, the demand for electronic document management systems is increasing. This significantly requires optimization of these systems in terms of quality document information retrieval and document management. However, research based on statistical methods cannot effectively handle large amounts of data extracted from electronic documents. In this regard, machine learning methods can effectively solve this problem. This paper presents an approach to building a model of an intelligent document management system using machine learning techniques to ensure efficient employee performance in organizations. The authors have solved a number of problems to optimize each of the document management subsystems, resulting in the development of an intelligent document management system model, which can be effectively applied to enterprises, government and corporate institutions. The feasibility and effectiveness of the proposed model of intelligent document management system based on machine learning and multi-agent modeling of information retrieval processes provides maximum reliability and reduced time of work on documents. The obtained results show that with the help of the presented model it is possible to further develop an intelligent document management system that will allow an electronic document to qualitatively go through the whole life cycle of a document, starting from the moment of document registration and finishing with its closing, i.e. execution, which will greatly facilitate the daily work of users with large volumes of documents. At the same time, the paper considers the application of topic modeling methods and algorithms of text analysis based on a multi-agent approach, which can be used to build an intelligent document management system.

This paper considers an approach to resolving referential relations when extracting information from a text. The proposed approach is an attempt to integrate the multifactorial model of the activation coefficient with the approach to resolving the referential ambiguity of the text when replenishing the ontology. The found objects are compared based on an assessment of the proximity of attributes and relationships of objects. An ontological interpretation of relations and measures of similarity of attributes based on a multifactorial model is proposed. This model is distinguished by the fact that it makes it possible to introduce the concepts of "rhetorical distance", "linear distance", "animation", "distance between paragraphs", and "syntactic and semantic role of the antecedent". A multifactorial model is proposed, which is a necessary and sufficient component for the purpose of explaining the measure of similarity of referents for choosing the best applicant. The counting system and its modification were revealed by trial and error; the work was carried out until the selected numerical weights began to explain all the available material. The current study also examines the factors of choice of reference devices that make it possible to work with complex sentences and texts. Moreover, examples of finding a measure of proximity in a multilingual system for the Kazakh, Russian, and English languages are offered. For the current paper, texts in the Russian, English, and Kazakh languages were used as a source for practical tasks. The texts were selected using news articles on the Internet sites where translations into other languages, including those named above, were offered. The authors of this study have done massive practical work, which confirms the correctness of the thesis they are considering.