SIVASANKARI. S.1, Gracia Jacob SHOMONA2
1 Anna University, SSN College of Engineering, Department of CSE,
Kalavakkam, Chennai-603110, India
2 SSN College of Engineering, Department of CSE, Kalavakkam,
Abstract: Ontology provides an organizational framework of concepts and a system that depicts hierarchical and associative relationships pertaining to an application domain. The possibility of reuse and data sharing permitted by ontology, along with the formal structure coupled with hierarchies of concepts and their inter-relationships offer the opportunity to draw complex inferences and reasoning. This rationale was the motivation to construct an ontology for Psoriasis Risk Assessment and Remedy (PRAR). This paper targets two issues: (i) Need for a medical database to derive Ontology (ii) Methodology for design of Semi-Automated Ontology Construction framework (SOCF) from pioneered data. Psoriasis is one of the most recurrent skin issues in India and the world at large and hence this paper targeted the need to generate a Psoriasis Remedy Database and automatically infer the relations between the Symptoms, Causes and Treatment through Semi-Automated Ontology Reasoning and Inference. The proposed system incorporated two phases: Formulation of a novel database for Psoriasis Risk Assessment Remedy (PRAR) (ii) Articulation of a novel framework for Psoriasis detection through computational modeling and Ontology Construction. The proposed methodology was tested on 112 samples from the authenticated UCI Machine Learning Repository. The ontology developed using the proposed SOCF mapped the risk factors and remedies for Psoriasis detection with 98.7% accuracy, this being reported for the first time.
Keywords: Psoriasis, OWL, XML, Mapping, Ontology, Reasoning, Inference.
CITE THIS PAPER AS:
SIVASANKARI. S., Gracia Jacob SHOMONA, A Novel Semi-Automated Ontology Construction Framework (SOCF) for Psoriasis Detection: Pioneering the Psoriasis Risk Assessment Remedy (PRAR) Database, Studies in Informatics and Control, ISSN 1220-1766, vol. 25(2), pp. 237-244, 2016.