Тип публикации: статья из журнала

Год издания: 2024

Идентификатор DOI: 10.1134/S1052618824700845

Ключевые слова: graph neural networks, integrated model, double deep Q-network method, reinforcement learning method, personalized recommender systems

Аннотация: A modern approach to personalized recommendation systems is presented, combining graph neural networks GNN with RL reinforcement learning methods. The GNN model is optimized for recommendation systems and is trained on vector representations of users and products, which are used to generate an initial list of recommendations that aПоказать полностьюre fed into the RL model. Particular attention is paid to the architecture and operation of the integrated GNN-RL model. The results of experimental studies demonstrating the effectiveness of the proposed approach are presented.

Журнал: Journal of Machinery Manufacture and Reliability

Выпуск журнала: Т. 53, № 8

Номера страниц: 980-986

ISSN журнала: 10526188

Место издания: Moscow

Издатель: Pleiades Publishing, Ltd.

• Sharifbaev A.N. (Moscow Institute of Physics and Technology (National Research University))
• Zainidinov H.N. (Tashkent University of Information Technologies)
• Kovalev I.V. (Siberian Federal University)
• Kravchenko I.N. (Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN))
• Kuznetsov Yu.A. (Parakhina Orel State Agrarian University)

• Ядро РИНЦ (eLIBRARY.RU)