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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Intellectual Movie Recommendation System Using Supervised Machine Learning Method
verfasst von : Priti Kumari, Vandana Dubey
Erschienen in: Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security
Verlag: Springer Nature Singapore
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Abstract
One of the AI applications that has attracted the most attention from researchers around the world is the recommendation system. Since the beginning of the Internet era, recommendation systems have been widely incorporated into our daily lives. It is still difficult to give new users the proper recommendations. This paper suggests a novel and sophisticated movie recommender model to address this problem and to suggest highly rated movies to the new users. Moreover, we have applied a number of supervised machine learning techniques, including as KNN, DT, RF, GNB, and LSVM, to evaluate the performance of the proposed model in terms of precision, recall, F1-score, and accuracy. In simulation, all the techniques are performing well on the proposed model and on the given datasets, however, the LSVM and GNB is proving higher accuracy along with precision, recall, and F1 measure.