Recommender system based on knowledges

Автор: Kurennykh Aleksei, Sudakov Vladimir

Журнал: Бюллетень науки и практики @bulletennauki

Рубрика: Технические науки

Статья в выпуске: 11 т.8, 2022 года.

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The article deals with the actual scientific and technical task of developing a recommender system that uses knowledge about the subject area for a more complete and accurate analysis of the problem situation. In the approach proposed by the authors, knowledge about the subject area is expressed by a computer model, which, under certain parameters, returns a vector of the simulation results. Both vectors of values are significant criteria on the basis of which recommendations are made. A special approach to the architecture of the information space, in which the interaction of recommender and modeling systems is implemented, provides ample opportunities for applying this approach in a wide class of problems.

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Recommender systems, computer simulation, data transfer

Короткий адрес: https://sciup.org/14125984

IDR: 14125984   |   DOI: 10.33619/2414-2948/84/45

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