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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM19795
Volume:
7 |
4 |
Apr 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Movie suggestion systems have gained significant popularity in recent years, as people increasingly seek personalized recommendations for their viewing choices. To provide these recommendations, machine learning algorithms are widely used. These systems analyse the user’s viewing history, ratings, and reviews, using techniques such as collaborative filtering, content-based filtering, and hybrid models. With the use of big data, these systems have become more accurate and efficient, providing users with a better movie watching experience. By leveraging machine learning techniques, movie suggestion systems are able to deliver relevant and precise recommendations to individual users, making the overall movie watching experience more enjoyable and satisfying.
KEYWORDS
Publication Date
4/28/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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