학술논문

Content-based Movie Recommendation System and Sentimental analysis using ML

Document Type

Conference

Author

Katkam, S.; Atikam, A.; Mahesh, P.; Chatre, M.; Kumar, S.S.; R, S.G.

Source

2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS) Intelligent Computing and Control Systems (ICICCS), 2023 7th International Conference on. :198-201 May, 2023

Subject

Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Machine learning algorithms
Filtering
Collaborative filtering
Process control
Machine learning
Programming
Motion pictures
Classification algorithms
Recommender systems
Python
content-based movie recommender system
Application programming interface key
K-Nearest Neighbor algorithm
Natural Language Processing
Cosine Similarity
Sentimental analysis
Naïve Bayes classifier

Language

ISSN

2768-5330

Abstract

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.

Online Access

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