Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Pacis, Lyndon Lee D."

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • No Thumbnail Available
    Publication
    Revolutionizing research discovery
    (Don Mariano Marcos Memorial State University - South La Union Campus, 2024-05) Pacis, Lyndon Lee D.; Aquino, Sean Carl B.; Cacayuran, Gemari M.; Fabros, Julie Ann S.; Fang, Felicity F.; Nario, Abegail G.
    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.

DSpace software copyright © 2002-2026 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback