참고문헌
- Bastian, M., S. Heymann, and M. Jacomy, 2009: Gephi: An open source software for exploring and manipulating networks. Proc., In Third international AAAI conference on weblogs and social media, San Jose, California, the Association for the Advancement of Artificial Intelligence, 2 pp.
- Blondel, V. D., J.-L. Guillaume, R. Lambiotte, and E. Lefebvre, 2008: Fast unfolding of communities in large networks. J. Stat. Mech.-Theory E., 10, P10008.
- Chae, Y., K. Cho, S. Lee, H. Jeon, Y. Chung, J. Lee, H. Park, and D.-K. Yoon, 2016: An analysis of the multiple impacts and policy networks of an extreme flood event in a metropolitan area. KEI 2016-14, 162 pp (in Korean).
- GTC, 2015: Big data analysis of disaster caused by climate change. Green Technology Center, 129 pp (in Korean).
- Gupta, V. and G. S. Lehal, 2009: A survey of text mining techniques and applications. J. Emerging Technologies in Web Intelligence, 1, 60-76.
- Hagberg, A. A., D. A. Schult, and P. J. Swart, 2008: Exploring network structure, dynamics, and function using NetworkX. Proc. The 7th Python in Science Conference (SciPy2008), 11-15.
- Jacomy, M., T. Venturini, S. Heymann, and M. Bastian, 2014: ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE, 9, e98679, doi:10.1371/journal.pone.0098679.
- Kim, D.-W., J.-H. Chung, J.-S. Lee, and J.-S. Lee, 2014: Characteristics of heat wave mortality in Korea. Atmosphere, 24, 225-234, doi:10.14191/Atmos.2014.24.2.225 (in Korean with English abstract).
- KCDC, 2016: Annual Report on the Notified Patients with Heat-related illness in Korea. Korea Centers for Disease Control and Prevention, 51 pp [Available online at http://www.nih.go.kr/contents.es?mid=a20304010700] (in Korean).
- MPSS, 2016: Statistical Yearbook of Natural Disaster 2015. Ministry of Public Safety and Security, 184 pp (in Korean).
- Mittermayer, M.-A., 2004: Forecasting Intraday Stock Price Trends with Text Mining Techniques. Proc.The 37th Hawaii International Conference on Social Systems, Hawaii, IEEE, 10 pp, doi:10.1109/HICSS.2004.1265201.
- Nassirtoussi, A. K., S. Aghabozorgi, T. Y. Wah, and D. C. L. Ngo, 2014: Text mining for market prediction: a systematic review. Expert Syst. Appl., 41, 7653-7670, doi:10.1016/j.eswa.2014.06.009.
- Newman, M. E. J., 2006: Modularity and community structure in networks. Proc. The National Academy of Sciences, 103, 8577-8582, doi:10.1073/pnas.0601602103.
- NIMS, 2011: Report on climate change scenario 2011. National Institute of Meteorological Sciences, 117 pp (in Korean).
- MOIS, 2017: Announcement of government-wide heat wave measures 2017. Ministry of the Interior and Safety, 15 pp (in Korean).
- Park, E. L., and S. Cho, 2014: KoNLPy: Korean natural language processing in Python. Proc. The 26th Annual Conference on Human & Cognitive Language Technology, SIGHCLT, 133-136 (in Korean).
- Park, S. B., 2012: Algal blooms hit South Korean rivers. Nature, doi:10.1038/nature 2012.11221.
- Rickman, T. A., and R. M. Cosenza, 2007: The changing digital dynamics of multichannel marketing: The feasibility of the weblog: text mining approach for fast fashion trending. J. Fashion Marketing and Management, 11, 604-621, doi:10.1108/13612020710824634.
- Sun, H., C. Lim, and Y. S. Lee, 2017: Analysis of the yearbook from the Korea Meteorological Administration using a text-mining algorithm. The Korean Journal of Applied Statistics, 30, 603-613, doi:10.5351/KJAS.2017.30.4.603 (in Korean with English abstract).
- Won, J.-Y., and D.-G. Kim, 2014: Deduction of social risk issues using text mining. J. Safety and Crisis Management, 10, 33-52 (in Korean with English abstract).
- WMO, 2015: WMO Guidelines on Multi-Hazard Impactbased Forecast and Warning Services. World Meteorological Organization, 23 pp.