期刊名称：Information Technology and Management Science
印刷版ISSN：2255-9086
电子版ISSN：2255-9094
出版年度：2015
卷号：18
期号：1
页码：129-134
DOI：10.1515/itms-2015-0020
语种：English
出版社：Walter de Gruyter GmbH
摘要：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.
关键词：classification ; decision tree ; ontology ; propositionalization ; taxonomy
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