文章基本信息

标题：Multilingual Medical Documents Classification Based on MesH Domain Ontology
本地全文：下载
作者：Elberrichi Zakaria ; Taibi Malika ; Belaggoun Amel 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：2
出版社：IJCSI Press
摘要：This article deals with the semantic Web and ontologies. It addresses the issue of the classification of multilingual Web documents, based on domain ontology. The objective is being able, using a model, to classify documents in different languages. We will try to solve this problematic using two different approaches. The two approaches will have two elementary stages: the creation of the model using machine learning algorithms on a labeled corpus, then the classification of documents after detecting their languages and mapping their terms into the concepts of the language of reference (English). But each one will deal with the multilingualism with a different approach. One supposes the ontology is monolingual, whereas the other considers it multilingual. To show the feasibility and the importance of our work, we implemented it on a domain that attracts nowadays a lot of attention from the data mining community: the biomedical domain. The selected documents are from the biomedical benchmark corpus Ohsumed, and the associated ontology is the thesaurus MeSH (Medical Subject Headings). The main idea in our work is a new document representation, the masterpiece of all good classification, based on concept. The experimental results show that the recommended ideas are promising.
关键词：multilingual classification; medical document; concept; domains ontology; Ohsumed; MeSH