Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Finding Naval Ship Maintenance Expertise Through Text Mining and SNA

  • Kim, Jin-Gwang (Dept. of Computer Science, Korea National Defense University) ;
  • Yoon, Soung-woong (Dept. of Computer Science, Korea National Defense University) ;
  • Lee, Sang-Hoon (Dept. of Computer Science, Korea National Defense University)
  • Received : 2019.04.30
  • Accepted : 2019.06.26
  • Published : 2019.07.31
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Abstract

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.

Keywords

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Fig. 1. Navy Ship’s Maintenance Process

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Fig. 3. Word Cloud(Maintenance detail)

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Fig. 4. Word Network(Maintenance detail)

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Fig. 5. Collaboration Relation Of Maintenance personnel

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Fig. 6. Collaboration Relation Group(2-mode Cohesion)

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Fig. 7. Network of EigenVector Centrality(Maintenance personnel-Maintenance detail)

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Fig. 8. Network of EigenVector Centrality(Maintenance person of P3, P7, P8 detail)

Table 1. Expert & Knowledge Management System

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Table 2. Rank of Collaboration Relation

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Table 3. EigenVector Centr of Maintenance personnel

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Table 4. Comparison of EigenVector Cent & PageRank

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Table 5. Comparison of Collabo Rel & EigenV Centr

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Table 6. Comparison of Text Mining & SNA

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