A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
The Knowledge Engineering Review
Artificial Intelligence in Medicine
Computational methods for Traditional Chinese Medicine: A survey
Computer Methods and Programs in Biomedicine
Text-based domain ontology building using tf-idf and metric clusters techniques
The Knowledge Engineering Review
An ontology-based similarity measurement for problem-based case reasoning
Expert Systems with Applications: An International Journal
A self-learning expert system for diagnosis in traditional Chinese medicine
Expert Systems with Applications: An International Journal
Lightweight community-driven ontology evolution
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Ontology development for unified traditional Chinese medical language system
Artificial Intelligence in Medicine
Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text
Artificial Intelligence in Medicine
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Traditional approach of ontology building interconnects people, place, objects and activities to represent the domain knowledge. It assumes that the knowledge rules in the ontology remains the same in any situations. However, in medicine domain, physicians always base on the problem situations to select the appropriate medical theories to perform diagnosis. So, the ontology developed with the traditional approach may not be suitable to be used as a knowledge base. Thus, a problem-driven approach of ontology building is proposed in order to capture the diagnostic knowledge and rules dynamically with the problem situations. This study applied the human cognitive model of problem solving and used the UMLS and OWL/SWRL to develop the traditional Chinese medicine diagnosis ontology. Since the ontology is built by interconnecting of people and knowledge on diagnostic decision making, it can be used as a knowledge base for medical diagnosis.