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http://dx.doi.org/10.7465/jkdi.2015.26.5.1105

Big data mining for natural disaster analysis  

Kim, Young-Min (Disaster Information Service Lab., Korea Institute of Science and Technology Information)
Hwang, Mi-Nyeong (Disaster Information Service Lab., Korea Institute of Science and Technology Information)
Kim, Taehong (Disaster Information Service Lab., Korea Institute of Science and Technology Information)
Jeong, Chang-Hoo (Disaster Information Service Lab., Korea Institute of Science and Technology Information)
Jeong, Do-Heon (Disaster Information Service Lab., Korea Institute of Science and Technology Information)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.5, 2015 , pp. 1105-1115 More about this Journal
Abstract
Big data analysis for disaster have been recently started especially to text data such as social media. Social data usually supports for the final two stages of disaster management, which consists of four stages: prevention, preparation, response and recovery. Otherwise, big data analysis for meteorologic data can contribute to the prevention and preparation. This motivated us to review big data technologies dealing with non-text data rather than text in natural disaster area. To this end, we first explain the main keywords, big data, data mining and machine learning in sec. 2. Then we introduce the state-of-the-art machine learning techniques in meteorology-related field sec. 3. We show how the traditional machine learning techniques have been adapted for climatic data by taking into account the domain specificity. The application of these techniques in natural disaster response are then introduced (sec. 4), and we finally conclude with several future research directions.
Keywords
Big data; data mining; machine learning; meteorologic data; natural disaster;
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