Paper Contents
Abstract
This study explores the challenges involved in using domain-specific ontologies to classify online content. Specifically, it focuses on applying the Medical Subject Headings (MeSH) thesaurus to improve the categorization of medical documents. Based on our findings, we propose a new content representation model. We compare our approach with traditional stem-based text encoding by employing two widely used data mining algorithms: C4.5 and K-Nearest Neighbors (KNN).
Copyright
Copyright © 2025 S.NARMATHA. This is an open access article distributed under the Creative Commons Attribution License.
Paper ID:
IJPREMS50700034451
ISSN:
2321-9653
Publisher:
ijprems