Theoretical and Natural Science

Theoretical and Natural Science

TNS Vol.2 (CIAP 2022), 02 February 2023

Open Access | Article

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

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, TNS Vol.2 (CIAP 2022), 161-171
Published 02 February 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yiting Yuan, Youyang Qin, Zekai Yu, Congbai Zhang. A Content-based Movie Recommendation System. TNS (2023) TNS Vol.2 (CIAP 2022): 161-171.


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.


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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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