FUZZY RELATIONS BASED INTELLIGENT INFORMATION RETRIEVAL FOR DIGITAL LIBRARY USERS

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.