Automatic generation of recommended systems based on qualitative interpretation of monitoring information

The article describes decision-making methods based on intelligent learning algorithms; for the construction of which verbal elements are used. Such algorithms and methods usually work in calculations with strictly quantitative data; however; taking into account the human way of perceiving information in verbal form. The person does not directly participate in the process of building the model; that is; its structure does not depend on expert or other human opinions; however; high-quality verbal information (for example; elements of regulations; documents; orders; etc.) is embedded in the algorithm in coded form. Computational experiments are presented.