A Semantic Analysis-Based Biomedical Repository and Research Recommendation System for Improving Research Discovery
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Keywords
database, digital repository, final project, query, search engine
Abstract
The rapid growth of biomedical research publications has created challenges for students and researchers in efficiently discovering relevant research topics and previous studies. Universities typically provide institutional repositories; however, access to department-specific final project collections is often limited. This study aims to develop a local biomedical repository and research recommendation system using a semantic analysis approach. The proposed system integrates an internal repository of final year projects with external academic databases, including IEEE Xplore and ScienceDirect, through Google Custom Search. Semantic analysis is applied to improve search relevance and generate research recommendations based on user queries and topic interests. The system was implemented as a web-based platform called BMEArchive. System evaluation was conducted using black-box testing and usability testing with the System Usability Scale (SUS) involving 10 student participants. The results show that the system achieved an average search and recommendation accuracy score of 86, while the usability evaluation produced a SUS score of 84.75, which falls into the “Excellent” category. These results indicate that the proposed system effectively assists students in discovering relevant biomedical research topics. Future work will focus on expanding the repository dataset and integrating advanced artificial intelligence and machine learning methods to improve recommendation accuracy.
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Norma Hermawan, Institut Teknologi Sepuluh Nopember
Biomedical Engineering Department