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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kolandaivel, P. Aggarwal, R. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Comput. Sci. & Software Eng., Concordia Univ., Montreal, Que. (Kolandaivel, P.) |
| Abstract | We present an expert system profile (EMIS) that serves as an information system for earthquake mitigation purpose. Knowledge-based systems, also called expert systems, are problem solving systems that use a knowledge base (KB) as one of their central components. Crucial phases for building an effective knowledge-base include data collection, knowledge acquisition and knowledge representation. In this paper, we first identify two main reasons for lack of effectiveness of available disaster management systems namely, lack of real data of the disaster and inability to appropriately extract as well as represent knowledge gained from such data in the disaster management system. Most disaster management systems assume that knowledge is provided by the experts, which may not always be possible. We explore data mining techniques to automate this process of knowledge acquisition. Further, such knowledge about natural catastrophes is highly uncertain due to the very nature of disasters. We make an attempt to manage and reason under uncertainty. Experimentation with real-life dataset show how our system allows users acquire information about earthquakes in the chosen area and mitigation steps required to be taken before, during and after such disasters |
| Starting Page | 337 |
| Ending Page | 340 |
| File Size | 105684 |
| Page Count | 4 |
| File Format | |
| ISBN | 1424400384 |
| DOI | 10.1109/CCECE.2006.277350 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-05-07 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Earthquakes Expert systems Electromagnetic interference Knowledge acquisition Data mining Information systems Knowledge based systems Problem-solving Knowledge representation Disaster management Knowledge Acquisition Expert System Knowledge base Uncertainty Bayesians Network |
| Content Type | Text |
| Resource Type | Article |
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