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

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.

Development of Commonsense Knowledge Modeling System for Psychological Assessment in Clinical Psycho

“…In this paper an approach was presented to model commonsense knowledge in psychological assessment for clinical psychology in Ayurvedic medicine evolved by dosa in Buddhist studies [43][44][45] using an Expert system based on principal component analysis and statistical fuzzy inference system. Dosa in Buddhist studies stated that ill-will, evil intention, wickedness, corruption and malice are various expressions and degrees of dosa and hateful temperament is said to be due to a predominance of the type of dosa, apo, vayu and semha.…”

Analyzing the disaster response competency of the local government official and the elected representative in Nepal

“…When it comes to the disaster response competency various researches have argued that the fundamental knowledge, disaster response preparedness and the responder's perception are the three primary pillars (Barsky et al 2007). Mendis et al (2007) had argued that the knowledge is the fundamental resource to enhance a function intelligently and if applied properly can provide a driving force for the action (Sallis and Jone 2002). Therefore special attention should be given to raise the knowledge and expertise of such local bodies so that they can prepare public services to function at the time of crisis (National Research Council 1991).…”

Knowledge model for emergency response based on contingency planning system of China

“…Much work has been done in the knowledge engineering (Altay & Pal, 2014;Singh, Dwivedi, Rana, Kumar, & Kapoor, 2017) for emergency management (Mendis, Karunananda, Samaratunga, & Ratnayake, 2007a;Yates & Paquette, 2011): ontology (Kollarits, Wergles, & Siegel, 2009), description logics (Grathwohl & de Beuvron, 1999), TTL (Hoogendoorn, Jonker, Popova, & Sharpanskykh, 2005), narrative networks (Constantinides & Barrett, 2012), fuzzy logic (Mendis, Karunananda, Samaratunga, & Ratnayake, 2007b), object-oriented constraint networks (Smirnov, Levashova, & Shilov, 2015), linguistic model (Zhang, Wang, & Zhao, 2018), space modeling (Xie, Li, Wei, Jiang, & Xie, 2016) and so on. Commonly, emergency management Dwivedi, Shareef, & Mukerji, 2017;Sinha, Kumar, Rana, Islam, & Dwivedi, 2017) includes four phases: mitigation, preparedness, response and recovery.…”