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An approach to the development of commonsense knowledge modeling systems for disaster management

An approach to the development of commonsense knowledge modeling systems for disaster management 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

An approach to the development of commonsense knowledge modeling systems for disaster management

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References (22)

Publisher
Springer Journals
Copyright
Copyright © 2009 by Springer Science+Business Media B.V.
Subject
Computer Science; Computer Science, general ; Artificial Intelligence (incl. Robotics)
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/s10462-009-9097-6
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Artificial Intelligence Review – Springer Journals

Published: Feb 26, 2009

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