A Content-based Movie Recommendation System

Research Article
Open access

A Content-based Movie Recommendation System

Yiting Yuan 1* , Youyang Qin 2 , Zekai Yu 3 , Congbai Zhang 4
  • 1 Yiting Yuan, Department of business, Rutgers University, Camden, NJ, 08102, United States    
  • 2 Youyang Qin, Abington Friends School, Jenkintown, PA, 19046, United States    
  • 3 Zekai Yu, Department of Statistics and Data Science, University of Washington, Seattle, 98105, United States    
  • 4 Congbai Zhang, Barry Florescue Undergraduate Business Program, University of Rochester, Rochester, NY, 14627, United States    
  • *corresponding author yy573@scarletmail.rutgers.edu
Published on 20 February 2023 | https://doi.org/10.54254/2753-8818/2/20220152
TNS Vol.2
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-915371-13-3
ISBN (Online): 978-1-915371-14-0

Abstract

In this paper, we describe a content-based movie recommendation system and provide an overview of the movie recommendation systems in today's market. Our findings show 1): Summary-Based and Feature-Based movie recommendation systems will provide different recommendation results. 2) Combined recommendation system’s result is consistent with the Summary-Based recommendation system but different from the Feature-Based recommendation system. Based on our recommendation system, we also made some innovations and fusion and conducted several control tests to improve the quality of our recommendations.

Keywords:

Yuan,Y.;Qin,Y.;Yu,Z.;Zhang,C. (2023). A Content-based Movie Recommendation System. Theoretical and Natural Science,2,56-66.
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References

[1]. Jena, A. (2022, March 17). Role of a movie recommender system in the streaming industry. Muvi One. Retrieved July 8, 2022, from https://www.muvi.com/blogs/movie-recommender-system.html

[2]. Sharma, L., & Gera, A. (n.d.). A Survey of Recommendation System: Research Challenges. Redirecting. Retrieved July 8, 2022, from https://answers.microsoft.com/en-us/windows/forum/all/cusersusernamedocumentsfile-folder-name/3c43589c-b582-433b-99ea-cfe3e1b2a270

[3]. Ahmed, M. (n.d.). Movie recommendation system using clustering and Pattern Recognition Network. IEEE Xplore. Retrieved July 8, 2022, from https://ieeexplore.ieee.org/document/8301695/

[4]. Uluyagmur, M. (n.d.). Content-based movie recommendation using different feature sets. Retrieved July 8, 2022, from http://www.iaeng.org/publication/WCECS2012/WCECS2012_pp517-521.pdf

[5]. Lops, P., Jannach, D., Musto, C., Bogers, T., & Koolen, M. (2019, March 7). Trends in content-based recommendation - user modeling and user-adapted interaction. SpringerLink. Retrieved July 8, 2022, from https://link.springer.com/article/10.1007/s11257-019-09231-w

[6]. Singh, R. H. (n.d.). Movie recommendation system using cosine similarity and KNN. Retrieved July 8, 2022, from https://www.researchgate.net/publication/344627182_Movie_Recommendation_System_using_Cosine_Similarity_and_KNN

[7]. Tewari, A. S., Singh, J. P., & Barman, A. G. (2018, June 8). Generating top-N items recommendation set using collaborative, content based filtering and rating variance. Procedia Computer Science. Retrieved July 1, 2022, from https://www.sciencedirect.com/science/article/pii/S1877050918308718

[8]. Wu, C.-S. M. (n.d.). Movie recommendation system using collaborative filtering. IEEE Xplore. Retrieved July 8, 2022, from https://ieeexplore.ieee.org/abstract/document/8663822

[9]. Keshava, M. C., Srinivasulu, S., Reddy, P. N., & Naik, B. D. (2020). Machine learning model for movie recommendation system. International Journal of Engineering Research & Technology (IJERT), 9(04).

[10]. Uddin, M. N. (n.d.). Enhanced content-based filtering using diverse collaborative prediction for movie recommendation. IEEE Xplore. Retrieved July 8, 2022, from https://ieeexplore.ieee.org/document/5175981

[11]. Afoudi, Y., Lazaar, M., & Achhab, M. A. (2021, July 24). Hybrid recommendation system combined content-based filtering and collaborative prediction using Artificial Neural Network. Simulation Modelling Practice and Theory. Retrieved July 1, 2022, from https://www.sciencedirect.com/science/article/pii/S1569190X21000836

[12]. Mubarak, S. (2021, August 18). Netflix dataset latest 2021. Kaggle. Retrieved July 8, 2022, from https://www.kaggle.com/datasets/syedmubarak/netflix-dataset-latest-202

[13]. Heidenreich, H. (2018, August 16). Introduction to word embeddings. Medium. Retrieved July 8, 2022, from https://towardsdatascience.com/introduction-to-word-embeddings-4cf857b12edc

[14]. Saket, S. (2020, January 12). Count vectorizers vs TFIDF vectorizers: Natural language processing. Medium. Retrieved July 8, 2022, from https://medium.com/artificial-coder/count-vectorizers-vs-tfidf-vectorizers-natural-language-processing-b5371f51a40c

[15]. Ahmed, I. (2020, May 16). Getting started with a movie recommendation system. Kaggle. Retrieved July 8, 2022, from https://www.kaggle.com/code/ibtesama/getting-started-with-a-movie-recommendation-system

[16]. Han, J., & Pei, J. (n.d.). Cosine similarity. Cosine Similarity - an overview | ScienceDirect Topics. Retrieved July 8, 2022, from https://www.sciencedirect.com/topics/computer-science/cosine-similarity

[17]. Dangeti, P. (n.d.). Statistics for Machine Learning. O'Reilly Online Learning. Retrieved July 8, 2022, from https://www.oreilly.com/library/view/statistics-for-machine/9781788295758/eb9cd609-e44a-40a2-9c3a-f16fc4f5289a.xhtml

[18]. Singh, Ramni & Maurya, Sargam & Tripathi, Tanisha & Narula, Tushar & Srivastav, Gaurav. (2020). Movie Recommendation System using Cosine Similarity and KNN. International Journal of Engineering and Advanced Technology. 9. 2249-8958. 10.35940/ijeat.E9666.069520.

Cite this article

Yuan,Y.;Qin,Y.;Yu,Z.;Zhang,C. (2023). A Content-based Movie Recommendation System. Theoretical and Natural Science,2,56-66.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2022)

ISBN：978-1-915371-13-3(Print) / 978-1-915371-14-0(Online)
Editor：Michael Harre, Marwan Omar, Roman Bauer
Conference website: https://www.confciap.org/
Conference date: 4 August 2022
Series: Theoretical and Natural Science
Volume number: Vol.2
ISSN：2753-8818(Print) / 2753-8826(Online)

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References

[1]. Jena, A. (2022, March 17). Role of a movie recommender system in the streaming industry. Muvi One. Retrieved July 8, 2022, from https://www.muvi.com/blogs/movie-recommender-system.html

[2]. Sharma, L., & Gera, A. (n.d.). A Survey of Recommendation System: Research Challenges. Redirecting. Retrieved July 8, 2022, from https://answers.microsoft.com/en-us/windows/forum/all/cusersusernamedocumentsfile-folder-name/3c43589c-b582-433b-99ea-cfe3e1b2a270

[3]. Ahmed, M. (n.d.). Movie recommendation system using clustering and Pattern Recognition Network. IEEE Xplore. Retrieved July 8, 2022, from https://ieeexplore.ieee.org/document/8301695/

[4]. Uluyagmur, M. (n.d.). Content-based movie recommendation using different feature sets. Retrieved July 8, 2022, from http://www.iaeng.org/publication/WCECS2012/WCECS2012_pp517-521.pdf

[5]. Lops, P., Jannach, D., Musto, C., Bogers, T., & Koolen, M. (2019, March 7). Trends in content-based recommendation - user modeling and user-adapted interaction. SpringerLink. Retrieved July 8, 2022, from https://link.springer.com/article/10.1007/s11257-019-09231-w

[6]. Singh, R. H. (n.d.). Movie recommendation system using cosine similarity and KNN. Retrieved July 8, 2022, from https://www.researchgate.net/publication/344627182_Movie_Recommendation_System_using_Cosine_Similarity_and_KNN

[7]. Tewari, A. S., Singh, J. P., & Barman, A. G. (2018, June 8). Generating top-N items recommendation set using collaborative, content based filtering and rating variance. Procedia Computer Science. Retrieved July 1, 2022, from https://www.sciencedirect.com/science/article/pii/S1877050918308718

[8]. Wu, C.-S. M. (n.d.). Movie recommendation system using collaborative filtering. IEEE Xplore. Retrieved July 8, 2022, from https://ieeexplore.ieee.org/abstract/document/8663822

[9]. Keshava, M. C., Srinivasulu, S., Reddy, P. N., & Naik, B. D. (2020). Machine learning model for movie recommendation system. International Journal of Engineering Research & Technology (IJERT), 9(04).

[10]. Uddin, M. N. (n.d.). Enhanced content-based filtering using diverse collaborative prediction for movie recommendation. IEEE Xplore. Retrieved July 8, 2022, from https://ieeexplore.ieee.org/document/5175981

[11]. Afoudi, Y., Lazaar, M., & Achhab, M. A. (2021, July 24). Hybrid recommendation system combined content-based filtering and collaborative prediction using Artificial Neural Network. Simulation Modelling Practice and Theory. Retrieved July 1, 2022, from https://www.sciencedirect.com/science/article/pii/S1569190X21000836

[12]. Mubarak, S. (2021, August 18). Netflix dataset latest 2021. Kaggle. Retrieved July 8, 2022, from https://www.kaggle.com/datasets/syedmubarak/netflix-dataset-latest-202

[13]. Heidenreich, H. (2018, August 16). Introduction to word embeddings. Medium. Retrieved July 8, 2022, from https://towardsdatascience.com/introduction-to-word-embeddings-4cf857b12edc

[14]. Saket, S. (2020, January 12). Count vectorizers vs TFIDF vectorizers: Natural language processing. Medium. Retrieved July 8, 2022, from https://medium.com/artificial-coder/count-vectorizers-vs-tfidf-vectorizers-natural-language-processing-b5371f51a40c

[15]. Ahmed, I. (2020, May 16). Getting started with a movie recommendation system. Kaggle. Retrieved July 8, 2022, from https://www.kaggle.com/code/ibtesama/getting-started-with-a-movie-recommendation-system

[16]. Han, J., & Pei, J. (n.d.). Cosine similarity. Cosine Similarity - an overview | ScienceDirect Topics. Retrieved July 8, 2022, from https://www.sciencedirect.com/topics/computer-science/cosine-similarity

[17]. Dangeti, P. (n.d.). Statistics for Machine Learning. O'Reilly Online Learning. Retrieved July 8, 2022, from https://www.oreilly.com/library/view/statistics-for-machine/9781788295758/eb9cd609-e44a-40a2-9c3a-f16fc4f5289a.xhtml

[18]. Singh, Ramni & Maurya, Sargam & Tripathi, Tanisha & Narula, Tushar & Srivastav, Gaurav. (2020). Movie Recommendation System using Cosine Similarity and KNN. International Journal of Engineering and Advanced Technology. 9. 2249-8958. 10.35940/ijeat.E9666.069520.

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