caa a22 4500 463207238 CHVBK 20180405153129.0 cr unu---uuuuu 170326e20070801xx s 000 0 eng 10.1007/s10462-009-9097-6 doi (NATIONALLICENCE)springer-10.1007/s10462-009-9097-6 An approach to the development of commonsense knowledge modeling systems for disaster management [Elektronische Daten] [D. Mendis, Asoka Karunananda, Udaya Samaratunga, Uditha Ratnayake] Knowledge is the fundamental resource that allows us to function intelligently. Similarly, organizations typically use different types of knowledge to enhance their performance. Commonsense knowledge that is not well formalized modeling is the key to disaster management in the process of information gathering into a formalized way. Modeling commonsense knowledge is crucial for classifying and presenting of unstructured knowledge. This paper suggests an approach to achieving this objective, by proposing a three-phase knowledge modeling approach. At the initial stage commonsense knowledge is converted into a questionnaire. Removing dependencies among the questions are modeled using principal component analysis. Classification of the knowledge is processed through fuzzy logic module, which is constructed on the basis of principal components. Further explanations for classified knowledge are derived by expert system technology. We have implemented the system using FLEX expert system shell, SPSS, XML, and VB. This paper describes one such approach using classification of human constituents in Ayurvedic medicine. Evaluation of the system has shown 77% accuracy. Springer Science+Business Media B.V., 2009 Knowledge modeling nationallicence Fuzzy logic nationallicence Expert systems nationallicence Ayurvedic medicine nationallicence Mendis D. Department of Information Technology, Advanced Technological Institute, Labuduwa, Sri Lanka aut Karunananda Asoka Faculty of Information Technology, University of Moratuwa, Katubedda, Moratuwa, Sri Lanka aut Samaratunga Udaya Gampaha Wickramarrachi Ayurveda Institute, University of Kelaniya, Ragama, Yakkala, Sri Lanka aut Ratnayake Uditha Department of Electrical and Computer Engineering, The Open University, Nawala, Nugegoda, Sri Lanka aut Artificial Intelligence Review Springer Netherlands 28/2(2007-08-01), 179-196 0269-2821 28:2<179 2007 28 10462 https://doi.org/10.1007/s10462-009-9097-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10462-009-9097-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Mendis D. Department of Information Technology, Advanced Technological Institute, Labuduwa, Sri Lanka aut NATIONALLICENCE 700 1- Karunananda Asoka Faculty of Information Technology, University of Moratuwa, Katubedda, Moratuwa, Sri Lanka aut NATIONALLICENCE 700 1- Samaratunga Udaya Gampaha Wickramarrachi Ayurveda Institute, University of Kelaniya, Ragama, Yakkala, Sri Lanka aut NATIONALLICENCE 700 1- Ratnayake Uditha Department of Electrical and Computer Engineering, The Open University, Nawala, Nugegoda, Sri Lanka aut NATIONALLICENCE 773 0- Artificial Intelligence Review Springer Netherlands 28/2(2007-08-01), 179-196 0269-2821 28:2<179 2007 28 10462 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer