“Analyzing User-Based and Item-Based Recommender Systems: A Comparative Examination”

Main Article Content

Dr. Divyesh P. Gohel
Dr. Pratik A. Vanjara


This research paper presents an in-depth analysis and comparative examination of two prominent recommender system approaches: user-based collaborative filtering and item-based collaborative filtering. Recommender systems play a pivotal role in enhancing user experiences by providing personalized recommendations. This study aims to dissect the mechanisms, strengths, and limitations of user-based and item-based methods, offering valuable insights for researchers and practitioners in the field. Through a comprehensive evaluation, we aim to shed light on the comparative effectiveness of these approaches in different scenarios and highlight considerations for their practical implementation.


Download data is not yet available.

Article Details

How to Cite
Dr. Divyesh P. Gohel, & Dr. Pratik A. Vanjara. (2024). “Analyzing User-Based and Item-Based Recommender Systems: A Comparative Examination”. Educational Administration: Theory and Practice, 30(6(S), 91–98. https://doi.org/10.53555/kuey.v30i6(S).5331
Author Biographies

Dr. Divyesh P. Gohel

Assistant Professor, Department of Computer Science & Information Technology, Atmiya University, Rajkot.

Dr. Pratik A. Vanjara

Head & Assistant Professor, Department of Computer Science, Shree M P Shah Commerce College, Surendranagar.