Merlarchive: A Web-Based Academic Hub for UDM With AI-Powered Natural Language Processing
Authors
College of Computing Studies, Universidad De Manila (Philippines)
College of Computing Studies, Universidad De Manila (Philippines)
College of Computing Studies, Universidad De Manila (Philippines)
College of Computing Studies, Universidad De Manila (Philippines)
Article Information
DOI: 10.51584/IJRIAS.2025.100900019
Subject Category: Information Technology
Volume/Issue: 10/9 | Page No: 213-229
Publication Timeline
Submitted: 2025-08-24
Accepted: 2025-08-30
Published: 2025-10-11
Abstract
Today, artificial intelligence (AI) is a critical technology in society, transforming the way people conduct work, communicate, and search for information. Natural Language Processing (NLP) is an important field within AI that allows computers to process and understand human language. Some common applications of NLP are chatbots, speech recognition, and voice assistants. In schools, NLP is particularly helpful for students because it streamlines their search process and helps them speed up their research by locating important related academic works without reading through each academic document. In the context of Universidad De Manila, many students and faculty struggled to locate thesis, research papers, and other academic works due to inefficient library systems that were tedious and unattractive to use. To resolve these issues, the proponents developed MerlArchive, which is an academic web hub based on AI/NLP. MerlArchive is a repository of digital research papers that is not only a storage and organizational system but also protects academic protection. Additionally, it has intelligent search capabilities like keyword search and voice search. Thus, MerlArchive enables students and faculty to spend less time researching academic works and allows them to spend more of their time focused on their studies or research. MerlArchive was developed in PHP and MySQL. In the development phase, the research team adopted a water fall plan. Additionally, MerlArchive is also organized by department and course, which should help to provide more accurate searching. A survey, which included students, faculty, and librarians using MerlArchive produced very good results, with an overall average of 4.75 out of 5 based on what users reported. Users expressed.
Keywords
Artificial Intelligence, Natural Language Processing, Digital Repository, Academic Research, Voice Search
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References
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