Deep Learning-based Automated Recommendation Systems: A Systematic Review and Trends
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Abstract
Recommender systems are progressively playing larger roles in a business’s transactions, profits, and overall success. This survey is intended to demonstrate the various aspects of recommender systems and their methodologies for implementation. As the purpose of a recommender system varies depending on the business’s necessities, its components and attributes vary accordingly. In this survey, important attributes of recommender systems are discussed, along with design guidelines. Some widely recognised methodologies are examined. Lastly, movie recommenders of the three most relevant domains, movies, music, and e-commerce, are introduced. The survey aims to give readers an expansive view of the situations in which certain recommender systems would be appropriate.
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