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Applying data mining for ontology building
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Abstract: Ontology represents the concepts and the relationship between them for specialized domain. Building ontology is a complex work, in order to build ontology you need a domain expert to help you to declare all domain concepts and the relationship between them. In this work we propose a methodology for building ontology based on the output of data mining result. We used c4.5 decision tree algorithm to discover and extract knowledge from structure data. Then we built ontology from the generated decision tree. We represent the generated ontology in XML and OWL languages. We work in two case studies; in the first case study we work in soybean diseases, and built ontology to represent the knowledge of diseases and their symptoms. In the second case study we work in animal diseases and extracted the knowledge related to them and we built ontology from the extracted knowledge.
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| URL |
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| Publication year |
2007
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| Organization Name |
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| City |
Cairo
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| serial title |
The 42nd Annual Conference On Statistics, Computer Science, and Operations Research
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| Author(s) from ARC |
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| External authors (outside ARC) |
Osman Hegazy
Faculty of Computers and Information, Information System Department, Cairo University Giza, Egypt
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AGROVOC
TERMS |
Expert systems.
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| Proposed Agrovoc |
Data mining;Ontology;Decision tree;
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| Publication Type |
Conference/Workshop
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