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Publikācija: Ontology-Based Classification System Development Methodology

Publication Type Publications in RTU scientific journal
Funding for basic activity Unknown
Defending: ,
Publication language English (en)
Title in original language Ontology-Based Classification System Development Methodology
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Pēteris Grabusts
Arkādijs Borisovs
Ludmila Aleksejeva
Keywords classification,decision tree, ontology, propositionalization, taxonomy
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.
DOI: 10.1515/itms-2015-0020
Reference Grabusts, P., Borisovs, A., Aleksejeva, L. Ontology-Based Classification System Development Methodology. Information Technology and Management Science. Vol.18, 2015, pp.129-134. ISSN 2255-9086. e-ISSN 2255-9094. Available from: doi:10.1515/itms-2015-0020
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