Pacis, Lyndon Lee D.Aquino, Sean Carl B.Cacayuran, Gemari M.Fabros, Julie Ann S.Fang, Felicity F.Nario, Abegail G.2025-09-192025-09-192024-05Pacis, L. L. D., Aquino, S. C. B., Cacayuran, G. M., Fabros, J. A. S., Fang, F. F., & Nario, A. G. (2024) Revolutionizing research discovery: A content-based recommendeder system for the DMMMMSU researches [Unpublished Undergraduate thesis]. Don Mariano Marcos Memorial State University - South La Union Campus, Agoo, La Union.https://lakasa.dmmmsu.edu.ph/handle/123456789/433Full text.Research discovery is a digital library that consists of concise and detailed information on the thesis/research of DMMMSU-SLUC. The repository features a contentbased recommender system built through machine learning, particularly naturaLlanguage processing, to suggest related studies based 011 user behavior. The study aimed to develop a Content-Based Recommender System for DMMMSU Researches. Specifically, researchers sought to: (1) develop a content-based recommender system for DMMMSU research using the Rapid Application Development Model; and (2) evaluate the usability of the proposed system using the lSO/IEC 9126 Software Quality Criteria. HTML, CSS, and JavaScript were used for the front-end; Python for modeling and data pre-processing; PHP and Xampp for server-side scripting. BERT achieved the highest similarity score compared to TF-IDF and BM25. Users could manage accounts, view/search research, and print/download studies. Administrators managed accounts, institutions, research, and granted access. The system was rated "Very Much Usable" by 420 respondents using ISO/lEC 9126 criteria.en-US