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AUTHOR(S): Siranush Sargsyan, Anna Hovakimyan, Varditer Keropyan
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TITLE An Approach to Developing and Implementing a Recommendation System |
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ABSTRACT The modern internet space provides the user with a huge amount of information, which is becoming more and more difficult to search. Recommendation systems are designed to provide information that best meets the needs of the user. Significant progress has been made in recent years in the development of proposal systems. The authors of the article have developed principles that use machine learning models to solve a number of problems in different areas. Methods are proposed, by means of which, having the objective characteristics of the subject domain, the solutions to some of the required problems are implemented. One of the tasks is to determine the quality criterion of the object and to give a proposal scenario for the creation of a high-quality object or product. The proposed set of models was used to predict the IMDB Movie Quality Assessment. Model experiments yielded relatively better results than [1]. |
KEYWORDS Recommendation system, AI, teaching sequence prediction, classifier, regression MSE և R2 metrics, IMDB Movie Quality Assessment |
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Cite this paper Siranush Sargsyan, Anna Hovakimyan, Varditer Keropyan. (2022) An Approach to Developing and Implementing a Recommendation System. International Journal of Economics and Management Systems, 7, 270-273 |
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