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A Study on the Reduction of Common Words to Classify Causes of Marine Accidents

해양사고 원인을 분류하기 위한 공통단어의 축소에 관한 연구

  • Yim, Jeong-Bin (Division of Navigation Sciences, Mokpo Maritime University)
  • Received : 2017.05.02
  • Accepted : 2017.06.23
  • Published : 2017.06.30

Abstract

The key word (KW) is a set of words to clearly express the important causations of marine accidents; they are determined by a judge in a Korean maritime safety tribunal. The selection of KW currently has two main issues: one is maintaining consistency due to the different subjective opinion of each judge, and the second is the large number of KW currently in use. To overcome the issues, the systematic framework used to construct KW's needs to be optimized with a minimal number of KW's being derived from a set of Common Words (CW). The purpose of this study is to identify a set of CW to develop the systematic KW construction frame. To fulfill the purpose, the word reduction method to find minimum number of CW is proposed using P areto distribution function and Pareto index. A total of 2,642 KW were compiled and 56 baseline CW were identified in the data sets. These CW, along with their frequency of use across all KW, are reported. Through the word reduction experiments, an average reduction rate of 58.5% was obtained. The estimated CW according to the reduction rates was verified using the Pareto chart. Through this analysis, the development of a systematic KW construction frame is expected to be possible.

주제어(key word, KW)는 해양사고의 주요한 원인을 간단하게 표현하기 위한 단어들의 집합으로 해양안전심판원의 심판관들이 작성한다. KW는 심판관들의 서로 다른 주관적인 견해 때문에 일관성 유지가 어렵고, KW의 수가 너무 많은 문제점이 있다. 이러한 문제를 해결하기 위해서는 최적화된 최소의 공통단어(common word, CW)를 이용한 체계적인 KW 구축 프레임이 필요하다. 본 연구의 목적은 체계적인 KW 구축 프레임 개발에 필요한 CW을 도출하는데 있다. 이러한 목적을 달성하기 위하여 본 연구에서는 파레토(Pareto) 분포함수와 파레토 지수를 이용한 최적의 최소 CW 도출방법을 제안하였다. 총 2,642개의 KW을 수집한 후, 수집한 KW의 세부 단어와 이들의 빈도를 갖는 데이터 세트에서 총 56개의 특징적인 CW를 식별하였다. 56개의 특징적인 CW를 이용한 단어 축소실험을 통해서 평균 58.5%의 축소율을 획득하였고, 축소율에 따라서 추정한 CW는 파레토 차트로 검증하였다. 이를 통해서 체계적인 KW 구축 프레임 개발이 가능할 것으로 기대된다.

Keywords

References

  1. Armour Philip, Burkhauser R. V. and Larrimore Jeff(2014), "Using the Pareto distribution to improve estimates of topcoded earnings", white paper, NBER WORKING PAPER SERIES, Working Paper 19846, pp. 1-18, http://www.nber.org/papers/w19846.
  2. Brynjolfsson Erik, Hu Yu and Simester Duncan(2007), "Goodbye Pareto Principle, Hello Long Tail: The Effect of Search Costs on the Concentration of Product Sales", white paper, version November 2007, pp. 1-39, http://ebusiness.mit.edu/research/papers/2007.11_Brynjolfsson_Hu_Simester_Goodbye%20Pareto%20Principle_276.pdf.
  3. Cho S. S., Jang E. J. and Yim, J. B.(2015), "Research on the Numerical Data Construction for Marine Accidents," Proc. of Spring Seminar 2015, Korean Institute of Navigation and Port Research, pp. 193-195
  4. Fialova Alena, Jureckova Jana and Picek Jan(2004), "Estimating Pareto tail index based on sample means", REVSTAT - Statistical Journal, Vol. 2, No. 1, pp. 75-100.
  5. Finkelstein M., Tucker G. H. and Veeh J. A.(2006), "Pareto tail index estimation revised," North American Actuarial Journal, Vol. 10, No. 1, pp. 1-10. https://doi.org/10.1080/10920277.2006.10596236
  6. IMO(1997), CODE FOR THE INVESTIGATION OF MARINE CASUALTIES AND INCIDENTS, Resolution A.849(20) adopted on 27 November 1997, Appendix : Guidelines to assist investigators in the implementation of the Code.
  7. Jang E. J., Kang Y. M. and Yim J. B.(2016), "On the Analysis of Key Word in Korea Maritime Safety Tribunal to Prevent Human Error in Maritime Accidents", KAOSTS Joint Seminar 2016, Program book of Journal of Korean Navigation and Port Research, pp. 196-198.
  8. KMST(2003), "Machinery damaged accident for fishing ship No. 77 Dong-Myeong HO", Accident Analysis Report by Eastern KMST, No. 2003-001
  9. KMST(2007), "Final report 2007 for the analysis of judged prejudication of Korea Maritime Safety Tribunal", pp. 1-366.
  10. KMST(2014), 2014 Statistical Annual Report to Maritime Causalities (2008-2014 combined), Korea Maritime Safety Tribunal, pp. 1-118.
  11. KMST(2015), Web site for the Investigation and Judgement Information Portal of Maritime Causalities, http://data.kmst.go.kr/kmst/verdict/verdictAbstract/selectVerdictAbstract.do.
  12. KMST(2016), "Final report 2016 for the analysis of judged prejudication of Korea Maritime Safety Tribunal", Pub. reg. number 11-1192251-000012-01, pp. 1-57.
  13. MOF(2013), Law for the Investigation and Judgement of Maritime Causalities, No. 11690
  14. Rytgaard M.(1990), "Estimation in the Pareto distribution", Astin Bulletin, Vol. 20, No. 2, pp. 201-216. https://doi.org/10.2143/AST.20.2.2005443
  15. Sousa D. B. and Michailidis George(2004), "A Diagnostic Plot for Estimating the Tail Index of a Distribution", Journal of Computational and Graphical Statistics, Vol. 13, No. 4, pp. 1-22. https://doi.org/10.1198/1061860043119
  16. Vilar-Zanon L. Jose and Lozano-Colomer Cristina(2007), "On Pareto conjugate priors and their application to large claims reinsurance premium calculation," Astin Bulletin, Vol. 37, No. 2, pp. 405-428. https://doi.org/10.1017/S0515036100014938
  17. Wikipedia(2016), Pareto index, http://en.wikipedia.org/wiki/Pareto_index.
  18. Yim, J. B.(2009a), Development of Quantitative Risk Assessment Methodology for the Maritime Transportation Accident of Merchant Ship, Journal of Korean Navigation and Port Research, Vol. 33, No. 1, pp. 9-19 https://doi.org/10.5394/KINPR.2009.33.1.009
  19. Yim, J. B.(2009b), Implementation Techniques for the Seafarer's Human Error Assessment Model in a Merchant Ship: Practical Application to a Ship Management Company, Journal of Korean Navigation and Port Research, Vol. 33, No. 3, pp. 181-191 https://doi.org/10.5394/KINPR.2009.33.3.181
  20. Yim J. B., Yang W. J. and Kim H. T.(2014), Maritime Accident Analysis - Maritime Accident Analysis and Prevention in the View Point of Ship Operation, Jeilkihok, Mokpo, pp. 1-391.