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논문 기본 정보

자료유형
학술저널
저자정보
Jin-Gwang Kim (Korea National Defense University) Soung-woong Yoon (Korea National Defense University) Sang-Hoon Lee (Korea National Defense University)
저널정보
한국컴퓨터정보학회 한국컴퓨터정보학회논문지 한국컴퓨터정보학회 논문지 제24권 제7호(통권 제184호)
발행연도
2019.7
수록면
125 - 133 (9page)

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초록· 키워드

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Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

목차

Abstract
I. Introduction
II. Related works
III. The Proposed Scheme
IV. Analysis Results
V. Conclusions
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