Provide a Recommender System for Predicting Users Favorite Music Using Gray Wolf Algorithm and Neural Networks

Recommender systems are systems that can recommend a good offer to users by taking limited information from users and features such as user searches in the past as well as data points. In this research, a new method is presented to suggest the favorite music of users. The proposed method of using the neural network and recommender system based on participatory filtering and using the points given by users to the products is discussed. We then optimize our data with the Gray Wolf algorithm. The results of the research show 95% accuracy of correct recommendations to users and it can be said that the proposed method of this research can greatly improve the problems of other previous methods and have good recommendations for users.

Author(s): Reza Molaee Fard

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