Ontology versus Semantic Networks for Medical Knowledge Representation

نویسندگان

  • ABDEL-BADEEH M. SALEM
  • MARCO ALFONSE
چکیده

The efficient Semantic Web, needs knowledge to be presented in a well defined form which enables people and software agents to understand it. There are many knowledge representation techniques such as rules, frames, scripts, semantic network and ontology. The purpose of this paper is to illustrate the difference between semantic network and ontology techniques for medical knowledge representation. The paper presents a development of semantic net and ontology for lung cancer using PROLOG and Protégé-OWL respectively. The results show that ontology supports representing knowledge semantically for building a robust knowledge-based system. Key-words: Knowledge Representation, Medical Informatics, Semantic Network, Ontology, Lung Cancer, Artificial Intelligence.

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تاریخ انتشار 2008