single-dr.php

JDR Vol.12 No.1 pp. 67-78
(2017)
doi: 10.20965/jdr.2017.p0067

Survey Report:

Disaster Information System Using Natural Language Processing

Naoko Kosaka*1,†, Akira Koyama*1, Tomohiro Kokogawa*1, Yuji Maeda*1, Hiroko Koumoto*2, Shingo Suzuki*3, Kenshi Yamaguchi*4, and Kentaro Inui*4

*1NTT Secure Platform Laboratories
3-9-11, Midori-cho Musashino-shi, Tokyo 180-8585, Japan

Corresponding author

*2Tokoha University, Shizuoka, Japan

*3National Research Institute for Earth Science and Disaster Resilience, Ibaraki, Japan

*4Tohoku University, Miyagi, Japan

Received:
August 10, 2016
Accepted:
January 13, 2017
Published:
February 1, 2017
Keywords:
natural language processing, incident response, activity log, SOP (Standard Operating Procedure)
Abstract
In this paper, we analyze incident response management work using free-formed information that is important for incident response communication. We develop a standard operating procedure for the work and study a support method based on a language processing technology to prevent missing or overlapping necessary tasks and optimize management of progress and integration management of related tasks. A prototype system was developed and evaluated in a workshop held by a local government, or in an exercise. As a result, it is confirmed that the use of language processing technology can make incident response management work efficient.
Cite this article as:
N. Kosaka, A. Koyama, T. Kokogawa, Y. Maeda, H. Koumoto, S. Suzuki, K. Yamaguchi, and K. Inui, “Disaster Information System Using Natural Language Processing,” J. Disaster Res., Vol.12 No.1, pp. 67-78, 2017.
Data files:
References
  1. [1] Cabinet Office, Government of Japan, “Report of standardization of measures for disaster recovery,” http://www.bousai.go.jp/kaigirep/kentokai/kentokaigi/pdf/report.pdf [accessed August 1, 2016, in Japanese]
  2. [2] Ministry of Land, Infrastructure, Transport and Tourism, “DiMAPS,” http://www.mlit.go.jp/saigai/dimaps/ [accessed August 1, 2016, in Japanese]
  3. [3] Institute of Scientific Approaches for fire and disaster, “Extinguishing fire and disaster prevention GIS,” http://www.isad.or.jp/cgi-bin/hp/index.cgi?ac1=IS25&ac2=&Page=hpd_view [accessed August 1, 2016, in Japanese]
  4. [4] N. Kosaka et al., “Study of Typical/Atypical Information Utilization According to Incident Response Phases on Emergency Management Support System,” IEICE Tech. Report, ICSSSL2014-15, October, 2014 (in Japanese).
  5. [5] K. Inui et al., “Computer-Assisted Databasing of Disaster Management Information Through Natural Language Processing,” J. of Disaster Research, Vol.10, No.5, pp. 830-844, 2015.
  6. [6] F. Ichinose et al., “A Fundamental Study of Efficiency of Information Processing in Emergency Operations Center,” J. of Disaster Research, Vol.9, No.2, pp. 206-214, 2014 (in Japanese).
  7. [7] F. Ichinose et al., “Evaluation of importance of treating free-style information in disaster information system and proposal for effective utilization method,” J. of Institute of Social Safety Science, No.27, pp. 179-188, 2015 (in Japanese).
  8. [8] FEMA, “General Message (ICS 213),” https://training.fema.gov/emiweb/is/icsresource/icsforms.htm [accessed August 1, 2016]
  9. [9] Homeland Security, Interoperability Continuum, “A tool for improving emergency response communication and interoperability,” http://www.dhs.gov/publication/commonly-accessed-documents-safecom [accessed August 1, 2016]
  10. [10] T. Hashimoto, T. Inui, and K. Murakami, “Constructing Extended Named Entity Annotated Corpora,” IPSJ Natural Language Processing (NL-188-17), pp. 113–120, 2008.
  11. [11] J. R. Finkel, T. Grenager, and C. Manning, “Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling, Proc. of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL 2005), pp. 363-370, 2005.
  12. [12] K. Matsuda, A. Sasaki, N. Okazaki, and K. Inui, “Annotating Geographical Entities on Microblog Text,” In Proc. of the 9th Linguistic Annotation Workshop (LAW IX 2015), pp. 85-94, June 2015.
  13. [13] C. D. Manning, P. Raghavan, and H. Schuetze, “Introduction to Information Retrieval,” Cambridge University Press, 2008.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 22, 2024