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Title: :  movie recommendation system
PaperId: :  20531
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 3 2023
DUI:    16.0415/IJARIIE-20531
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
vaibhav tyagiinderprastha engineering college
vidhi sharmainderprastha engineering college
yashila samanthrayinderprastha engineering college

Abstract

computer science engineering
Movie Recommendation System, Machine Learning, Content-Based Filtering, Personalized Recommendations, Python, Scikit-Learn, Evaluation Metrics, Kaggle Dataset.
The exponential growth of the internet and the increasing popularity of online video streaming platforms have resulted in a vast amount of video content available on the web. With this enormous amount of content, movie recommendation systems have become an essential component of these platforms to aid users in finding relevant and personalized content. In recent years, machine learning techniques have shown to be an effective tool for building recommendation systems, particularly collaborative filtering and content-based filtering techniques.In this research paper, we present a movie recommendation system using machine learning algorithms. The system is designed to provide personalized movie recommendations to users based on their viewing history, preferences, and ratings. The proposed system uses collaborative filtering and content-based filtering techniques to provide movie recommendations to users. The system is developed using Python programming language and scikit-learn machine learning library. The system is evaluated using the MovieLens dataset, which contains movie ratings by users. The performance of the system is measured using various evaluation metrics, including mean absolute error (MAE), root mean squared error (RMSE), and precision-recall curve. The results show that the proposed system provides accurate and personalized movie recommendations to users.Overall, the proposed movie recommendation system using machine learning algorithms demonstrates the effectiveness of machine learning techniques in building personalized recommendation systems. The system can be integrated into online video streaming platforms to improve user experience and satisfaction by providing personalized and relevant movie recommendations.

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IJARIIE vaibhav tyagi, vidhi sharma, and yashila samanthray. "movie recommendation system" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 3 2023 Page 2815-2818
MLA vaibhav tyagi, vidhi sharma, and yashila samanthray. "movie recommendation system." International Journal Of Advance Research And Innovative Ideas In Education 9.3(2023) : 2815-2818.
APA vaibhav tyagi, vidhi sharma, & yashila samanthray. (2023). movie recommendation system. International Journal Of Advance Research And Innovative Ideas In Education, 9(3), 2815-2818.
Chicago vaibhav tyagi, vidhi sharma, and yashila samanthray. "movie recommendation system." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 3 (2023) : 2815-2818.
Oxford vaibhav tyagi, vidhi sharma, and yashila samanthray. 'movie recommendation system', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, 2023, p. 2815-2818. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/movie_recommendation_system_ijariie20531.pdf (Accessed : ).
Harvard vaibhav tyagi, vidhi sharma, and yashila samanthray. (2023) 'movie recommendation system', International Journal Of Advance Research And Innovative Ideas In Education, 9(3), pp. 2815-2818IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/movie_recommendation_system_ijariie20531.pdf (Accessed : )
IEEE vaibhav tyagi, vidhi sharma, and yashila samanthray, "movie recommendation system," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 3, pp. 2815-2818, May-Jun 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/movie_recommendation_system_ijariie20531.pdf [Accessed : ].
Turabian vaibhav tyagi, vidhi sharma, and yashila samanthray. "movie recommendation system." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 3 ().
Vancouver vaibhav tyagi, vidhi sharma, and yashila samanthray. movie recommendation system. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(3) : 2815-2818. Available from: https://ijariie.com/AdminUploadPdf/movie_recommendation_system_ijariie20531.pdf
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