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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Emmanuel B. Adigun
Covenant University Ota
Computer Science & IT

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Semantics-based clustering approach for similar research area detection Marion Oluwabunmi Adebiyi; Emmanuel B. Adigun; Roseline Oluwaseun Ogundokun; Abidemi Emmanuel Adeniyi; Peace Ayegba; Olufunke O. Oladipupo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.15001

Abstract

The manual process of searching out individuals in an already existing research field is cumbersome and time-consuming. Prominent and rookie researchers alike are predisposed to seek existing research publications in a research field of interest before coming up with a thesis. From extant literature, automated similar research area detection systems have been developed to solve this problem. However, most of them use keyword-matching techniques, which do not sufficiently capture the implicit semantics of keywords thereby leaving out some research articles. In this study, we propose the use of Ontology-based pre-processing, Latent Semantic Indexing and K-Means Clustering to develop a prototype similar research area detection system, that can be used to determine similar research domain publications. Our proposed system solves the challenge of high dimensionality and data sparsity faced by the traditional document clustering technique. Our system is evaluated with randomly selected publications from faculties in Nigerian universities and results show that the integration of ontologies in preprocessing provides more accurate clustering results.
Co-Authors Abidemi Emmanuel Adeniyi Marion Oluwabunmi Adebiyi Olufunke O. Oladipupo Peace Ayegba Roseline Oluwaseun Ogundokun