• Journal of KIISE:Software and Applications
• /
• v.35 no.6
• /
• pp.366-373
• /
• 2008

The web ontology language(OWL) has been used by ontology designers to construct ontology. In order to derive hidden information(concept subsumption, concept satisfiability and realization) of OWL ontology, a number of OWL reasoners have been introduced. But most reasoners simply report these information without process for any arbitrary entailment and unsatisfiable concept derived from a OWL ontologies. In this paper, we propose Minimum Expression Axiom Set(MEXS) detection and storing for debugging unsatisfiable concepts in ontology. In order to detect MEXS, we need to find axiom to cause inconsistency in ontology. Therefore, our work focused on two key aspects: given a inconsistency ontology, identifying the roots of axioms to occur unsatisfiable and derived axioms from among them; and extracting MEXS. Our results can be applicable to all application, which is at the basis of the description logic.

• Journal of KIISE:Software and Applications
• /
• v.35 no.12
• /
• pp.764-773
• /
• 2008

The web ontology language(OWL) has become a W3C recommendation to publish and share ontologies on the semantic web. In order to check the satisfiablity of concepts in OWL ontology, OWL reasoners have been introduced. But most reasoners simply report check results without providing a justification for any arbitrary entailment of unsatisfiable concept in OWL ontologies. In this paper, we propose dependency label based causing inconsistency axiom (CIA) detection for debugging unsatisfiable concepts in ontology. CIA is a set of axioms to occur unsatisfiable concepts. In order to detect CIA, we need to find axiom to cause inconsistency in ontology. If precise CIA is gave to ontology building tools, these ontology tools display CIA to debug unsatisfiable concepts as suitable presentation format. Our work focuses on two key aspects. First, when a inconsistency ontology is given, it detect axioms to occur unsatisfiable and identify the root of them. Second, when particular unsatisfiable concepts in an ontology are detected, it extracts them and presents to ontology designers. Therefore we introduce a tableau-based decision procedure and propose an improved method which is dependency label based causing inconsistency axiom detection. Our results are applicable to the very expressive logic SHOIN that is the basis of the Web Ontology Language.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.06a
• /
• pp.93-94
• /
• 2007

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.343-351
• /
• 2001

World practice is evidence of that computer systems of an intellectual support of medical activities bound up with examination of patients, their diagnosis, therapy and so on are the most effective means for attainment of a high level of physician\`s qualification. Such systems must contain large knowledge bases consistent with the modern level of science and practice. To from large knowledge bases for such systems it is necessary to have a medical ontology model reflecting contemporary notions of medicine. This paper presents a description of an observation ontology, knowledge base for the physician of general tipe, architecture, functions and implementation of problem independent shell of the system for intellectual supporting patient examination and mathematical model of the dialog. The system can be used by the following specialist: therapeutist, surgeon, gynecologist, urologist, otolaryngologist, ophthalmologist, endocrinologist, neuropathologist and immunologist. The system supports a high level of examination of patients, delivers doctors from routine work upon filling in case records and also automatically forms a computer archives of case records. The archives can be used for any statistical data processing, for producing accounts and also for debugging of knowledge bases of expert systems. Besides that, the system can be used for rise of medical education level of students, doctors in internship, staff physicians and postgraduate students.