Ontology-Based Classification System Development Methodology
2015
Pēteris Grabusts, Arkādijs Borisovs, Ludmila Aleksejeva

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.


Keywords
classification,decision tree, ontology, propositionalization, taxonomy

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.

Publication language
English (en)
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