Content-based Movie Recommendation System and Sentimental analysis using ML

The recommendation system is important in today's world and is employed by many famous apps. A recommendations system is one that suggests books, movies, music, and other resources to users based on a data collection. Typically, movie recommendation algorithms anticipate what movies a user woul...

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Bibliographic Details
Published in:	2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS) pp. 198 - 201
Main Authors:	Katkam, Saketh, Atikam, Abhishek, Mahesh, Pallerla, Chatre, Mrunal, Kumar, Shree Sai, R, Sakthidharan G
Format:	Conference Proceeding
Language:	English
Published:	IEEE 17-05-2023
Subjects:	Application programming interface key Classification algorithms Collaborative filtering content-based movie recommender system Cosine Similarity Filtering K-Nearest Neighbor algorithm Machine learning Machine learning algorithms Motion pictures Natural Language Processing Naïve Bayes classifier Process control Programming Python Recommender systems Sentimental analysis
Online Access:	Get full text
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Summary:	The recommendation system is important in today's world and is employed by many famous apps. A recommendations system is one that suggests books, movies, music, and other resources to users based on a data collection. Typically, movie recommendation algorithms anticipate what movies a user would enjoy based on the characteristics of previously loved movies. The algorithms can propose movies based on one or more criteria such as the genre of the film, the people in it, or even the director of the film. The method used is content-based filtering with genre correlation.
ISSN:	2768-5330
DOI:	10.1109/ICICCS56967.2023.10142424