It is known that today information and library systems are one of the main sources of information needs of the population and have many users. Information and library systems have a large amount of valuable information resources and information retrieval services have been established to allow users to find the necessary literature. We know that search engines take requests and return results they think are relevant. As a result, the user again faces the problem of finding what he needs among the many sources of information provided.Today, a number of information systems effectively use recommendation systems based on artificial intelligence to recommend objects. In information and library systems, high efficiency can be achieved by identifying the information needs of users and recommending relevant literature.To do this, it is necessary to determine the information needs of library users by analyzing information about their age, interests, level of knowledge in a particular area, previous requests, professions, etc. By introducing recommender systems into library information systems, it is possible to facilitate the work of librarians, increase speed and accuracy finding the necessary source of information, increase the efficiency of management and the level of satisfaction of the information needs of the population.The article proposes a fuzzy model for solving the problem of assessing the needs of users of information and library systems and recommending relevant literature to them.

The relevance of creating information systems using artificial intelligence methods and tools is dictated by the following reasons: The volume of scientific and educational information is growing; Traditional information retrieval methods have exhausted themselves. Using only deterministic and iteration methods, rigid algorithms don't give the expected results. They require more time to process information and more memory. Significant progress in recent years in the development of artificial intelligence (AI) methods and systems gives hope that their use will significantly reduce the time needed to search for data for scientific research and educational activities. The aim of the research results presented in the article is to increase the efficiency for scientific and educational information retrieval based on the use of AI methods implemented in the integrated intelligent information system “SMART TUIT". The article presents the results of theoretical and applied research obtained by several departments of the Tashkent University of Information Technology (TUIT) in solving the following tasks: Voice recognition for subsequent processing; Pattern recognition in order to identify the users of information; Search and processing of scientific and educational resources in electronic libraries; Analysis of information needs of users depending on the level of competence and type of activity; Evaluation of scientific and educational information to identify the most important data sources; Geoinformation system to solve the problems of the location of the information source. Initially, each research area in the departments was aimed at solving a certain class of problems related to medicine, linguistics, electronic libraries, corporate networks, information security systems, etc. The TUIT creative group decided to combine efforts to apply the results obtained to solve the important problem of intellectualizing the search for sources of scientific and educational information among a large amount of data.

The complexity of modern social communications and the transformation of society's information environment create unique competition among public digital libraries to attract readers. Library websites play an important role in managing the activities of digital libraries and improving their position in the information space. In general, the website is considered the "calling card" of the electronic library. It is not only a means of communication between readers and the library, but also a source of information that allows you to evaluate the activities of the library based on information about the use of library website by readers. The purpose of the study is to develop a data processing method to improve the efficiency of evaluating public library information resources and websites. A method and algorithm for expert assessment of a site using fuzzy logic are proposed. The article presents the possibilities of using web analytics to determine webometric indicators of a library website, study user behavior patterns, as well as analysis that improves the functionality of the site. Libraries are offered a comprehensive method for multi-criteria evaluation of websites. The essence of this method is that with this method we can not only evaluate the website in a traditional way, but also get the following useful results: full evaluation of websites, evaluation of websites according to certain criteria, selective comparison and ranking of websites are presented. An analysis of classification criteria for evaluating public library websites is presented. To minimize subjectivity when evaluating a website, the evaluation process can involve not only experts, but also a wider audience through online and offline surveys. In general, assessment of electronic public library websites is necessary not only to determine the rating of libraries, but also to make the right management decisions, as well as to determine the needs and interests of readers.

Mobile RFID inventory in libraries must be planned and evaluated under noisy observations, configuration-dependent read regimes, and incomplete supervision. This paper presents an uncertainty-aware analytics framework for robot-assisted RFID inventory using the public RFID Location dataset. The framework has three phases. Phase 1 converts irregular list-encoded logs into atomic RFID events and quantifies how operating configuration changes read density and signal variability. Phase 2 performs map-constrained Bayesian shelf inference by synchronizing RFID reads with robot trajectory and antenna geometry and by fusing RSSI and carrier phase over feasible shelf candidates. Phase 3 translates posterior spread and non-convergence into proxy review workload and cost, enabling configuration comparison and certainty–throughput trade-off analysis when strict EPC-to-item linkage is unavailable. Across 688,073 aligned RFID observations, the pipeline produces 18,190 posterior tag estimates from five inventory runs. The empirical results show strong run dependence: the best run achieves a mean posterior spread of 0.906 m with a convergence rate of 0.553, whereas a degraded run reaches only 0.004 convergence with a mean spread above 2.1 m. Because EPC-to-item linkage is unavailable, these values are posterior concentration and workload indicators rather than ground-truthed localization-accuracy metrics. A saved phase-weight ablation further shows that adding phase information substantially sharpens posterior concentration relative to an RSSI-only baseline. Under the proxy workload model, autonomous-S1-P30 provides the most favorable balance among posterior certainty, scan effort, and implied review burden.

Access to valuable scientific and educational resources is an important aspect of the effectiveness of the educational process. Depending on their financial capabilities, academic libraries subscribe to various databases of the world's leading publishers. It is very important to evaluate certain databases in order to select the necessary sources of information for educational and scientific activities. The purpose of the article is to determine the most important criteria for evaluating scientific and educational databases in academic libraries based on a survey conducted among teachers and students of technical universities of the Republic of Uzbekistan. The key criteria are content relevance, thematic coverage, usability, accessibility, technical specifications, licensing models, and scalability to meet future needs. The study emphasizes the importance of aligning database selection with institutional research priorities, user accessibility requirements, and emerging fields of study. Additionally, the role of open-access resources, interdisciplinary content, and vendor support in decision-making is analyzed. By developing a comprehensive framework for database evaluation, this article provides valuable insights for librarians and academic institutions seeking to optimize their resource offerings and support diverse research endeavors.

This article is devoted to the analysis of methods for creating a knowledge base of a digital library based on the semantic model of authority files. The article also describes the practical aspects of creating an electronic library legal encyclopedia based on the semantic model of authority files. Creation of a semantic network of authority files significantly optimizes the quality and speed of searching for resources in electronic libraries and creates the basis for intellectualization of information retrieval. The article examines in detail the existing approaches to creating a knowledge base of authority files, including files based on semantic models, and forming a knowledge base structure. The main purpose of the study is to create an improved model and develop software for creating a knowledge base of an electronic library of semantic authority files for various subject areas. In the article the theoretical research methods (method of comparison and critical thinking) and empirical research methods (data collection and document analysis) have been applied. Used object-oriented programming, intelligent information retrieval, reverse indexing capabilities. The field of jurisprudence was chosen for the application and approbation of the created model and software. A knowledge base has been created that studies frequently used specialized terms and semantic relationships between them.