Ontology-Based Classification System Development Methodology

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 attrib...

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Bibliographic Details
Published inInformation Technology and Management Science Vol. 18; no. 1; pp. 129 - 134
Main Authors Grabusts, Peter, Borisov, Arkady, Aleksejeva, Ludmila
Format Journal Article
LanguageEnglish
Published De Gruyter Open 01.12.2015
RTU PRESS
Subjects
classification
decision tree
ontology
propositionalization
taxonomy
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Summary: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.
ISSN:2255-9094
2255-9094
DOI:10.1515/itms-2015-0020