Ontology-Based Classification System Development Methodology

Grabusts Peter (), Borisov Arkady () and Aleksejeva Ludmila ()
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Grabusts Peter: Rezekne Higher Educational Institution
Aleksejeva Ludmila: Riga Technical University

Information Technology and Management Science, 2015, vol. 18, issue 1, 129-134

Abstract: The aim of the article is to analyse and develop an ontology-based classification system methodology that uses decision tree learning with statement propositionalized attributes. Classical decision tree learning algorithms, as well as decision tree learning with taxonomy and propositionalized attributes have been observed. Thus, domain ontology can be extracted from the data sets and can be used for data classification with the help of a decision tree. The use of ontology methods in decision tree-based classification systems has been researched. Using such methodologies, the classification accuracy in some cases can be improved.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:itmasc:v:18:y:2015:i:1:p:129-134:n:20

DOI: 10.1515/itms-2015-0020

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