Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)

<Previous Article In Volume
Next Article In Volume>

Content Based Recommendation System on Movies

Authors
D. Phani Kumar1, *, Animesh Kumar Singh1, Sai Neha Arepu1, Manideep Sarvasuddi1, Erragatla Gowtham1, Yalamanchili Sanjana1
1Godavari Institute of Engineering and Technology, Rajamahendravaram, India
*Corresponding author. Email: phanikumar@giet.ac.in
Corresponding Author
D. Phani Kumar
Available Online 9 November 2023.
DOI
10.2991/978-94-6463-252-1_49How to use a DOI?
Keywords
Movie; recommendation system; content-based; Count Vectorizer; Porter Stemmer; Cosine Similarity; Machine Learning Algorithms
Abstract

Today's competitive environment makes it necessary for suggestive advice to be made to the user for them to continue using the services they currently find enjoyable. There, the recommender system's function assumes a key role. Every service in today's world has a recommendation system for movies, music, e-commerce, etc. The Netflix recommender system is essential for increasing the customer experience when watching movies on the service. This research proposes a machine learning-based content-based recommender system for movie recommendations. Examining the movie-enabling recommendations using data from the Tmdb, movies dataset from Kaggle. We use algorithms like Count Vectorizer, Porter Stemmer, and Cosine Similarity to generate five similar movies closely related to the type of content the target movie has and how well our machine-learning approach is working.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
Series
Advances in Engineering Research
Publication Date
9 November 2023
ISBN
10.2991/978-94-6463-252-1_49
ISSN
2352-5401
DOI
10.2991/978-94-6463-252-1_49How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - D. Phani Kumar
AU  - Animesh Kumar Singh
AU  - Sai Neha Arepu
AU  - Manideep Sarvasuddi
AU  - Erragatla Gowtham
AU  - Yalamanchili Sanjana
PY  - 2023
DA  - 2023/11/09
TI  - Content Based Recommendation System on Movies
BT  - Proceedings of the Second International Conference on Emerging Trends in Engineering (ICETE 2023)
PB  - Atlantis Press
SP  - 462
EP  - 472
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-252-1_49
DO  - 10.2991/978-94-6463-252-1_49
ID  - Kumar2023
ER  -