Year: 2012
Type: preprint
Abstract: This paper addresses the problem of classifying web documents using domain ontology. Our goal is to provide a method for improving the classification of medical documents by exploiting the MeSH thesaurus (Medical Subject Headings) which will allow us to generate a new representation based on concepts. This approach was tested with two well-known data mining algorithms C4.5 and KNN, and a comparison was made with the usual representation using stems. The enrichment of vectors using the concepts and the hyperonyms drawn from the domain ontology has significantly boosted their representation, something essential for good classification. The results of our experiments on the benchmark biomedical collection Ohsumed confirm the importance of the approach by a very significant improvement in the performance of the ontology-based classification compared to the classical representation (Stems) by 30%.
Source: arXiv (Cornell University)
Institution: Université Djilali de Sidi Bel Abbès
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1582862293