Movie Recommendation System Using User-Based Collaborative Filtering (ubcf)
Student: Abdulmalik Kaka Musa (Project, 2025)
Department of Computer Information and Communication Science
Federal University, Dutsin-Ma, Katsina State
Abstract
This project presents the development of a movie recommendation system using User-Based Collaborative Filtering (UBCF). The system is designed to alleviate the problem of information overload and enhance user satisfaction on movie streaming platforms. Using the MovieLens 100K dataset, the system identifies user preferences through rating patterns and recommends movies based on similarities computed with Pearson Correlation. The project was implemented in Python using libraries such as Pandas and Scikit-learn. Evaluation metrics such as Precision (0.82), Recall (0.75), and F1-Score (0.78) demonstrate the effectiveness of the system. Though limited by cold-start and sparsity issues, the results show promising potential for lightweight recommendation systems in real-world applications.
Keywords
For the full publication, please contact the author directly at: abdulmalikmusakaka@gmail.com
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Institutions
- Al-Hikmah University, Ilorin, Kwara State 2
- AL-ISTIQAMAH UNIVERSITY, SUMAILA, KANO STATE 1
- Al-Qalam University, Katsina, Katsina State 5
- Alex Ekwueme Federal University, Ndufu-Alike, Ebonyi State 87
- Alvan Ikoku College of Education, Imo State, (Affl To Univ of Nigera, Nsukka) 11
- Ambrose Alli University, Ekpoma, Edo State 479
- Anambra State College of Health Technology, Obosi, Anambra State 1
- Auchi Polytechnic, Auchi, Edo State 503
- Auchi Polytechnic, Auchi, Edo State. (affl To Nnamdi Azikiwe University, Awka) 3
- Audu Bako College of Agriculture Danbatta, Kano, Kano State 54