DEVELOPMENT OF A RECOMMENDER SYSTEM FOR THE SELECTION OF LITERATURE
Y.D. OSIPOVA, O.N. KANEVA · Applied Mathematics and Fundamental Informatics · 2024
The article discusses the design and implementation of building recommendations in the web application of an online library. Such methods of building recommendations as content and collaborative filtering and possible options for their implementation are being investigated. Among the options studied are machine learning methods such as clustering and regression, represented by thematic modeling and prediction of pre-readings, and the article describes the algorithms underlying each of the selected methods, as well as presents the results of the obtained models. The developed solution is implemented as an online library service and helps users to find the literature they are interested in among the books posted on the resource.