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http://dx.doi.org/10.3745/KTSDE.2020.9.10.317

Analysis of Disaster Safety Situation Classification Algorithm Based on Natural Language Processing Using 119 Calls Data  

Kwon, Su-Jeong ((주)넥타르소프트)
Kang, Yun-Hee (백석대학교 ICT학부)
Lee, Yong-Hak ((주)넥타르소프트)
Lee, Min-Ho ((주)넥타르소프트)
Park, Seung-Ho ((주)넥타르소프트)
Kang, Myung-Ju ((주)넥타르소프트 연구소)
Publication Information
KIPS Transactions on Software and Data Engineering / v.9, no.10, 2020 , pp. 317-322 More about this Journal
Abstract
Due to the development of artificial intelligence, it is used as a disaster response support system in the field of disaster. Disasters can occur anywhere, anytime. In the event of a disaster, there are four types of reports: fire, rescue, emergency, and other call. Disaster response according to the 119 call also responds differently depending on the type and situation. In this paper, 1280 data set of 119 calls were tested with 3 classes of SVM, NB, k-NN, DT, SGD, and RF situation classification algorithms using a training data set. Classification performance showed the highest performance of 92% and minimum of 77%. In the future, it is necessary to secure an effective data set by disaster in various fields to study disaster response.
Keywords
Artificial Intelligence; Emergency Response; Natural Language Processing; Situation Classification; Machine Learning;
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