대한산업공학회지 (Journal of Korean Institute of Industrial Engineers)

  • 제40권1호
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  • Pages.52-59
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  • 2014
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  • 1225-0988(pISSN)
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  • 2234-6457(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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텍스트 마이닝을 이용한 산업공학 연구기법의 분석

An Analysis of the Research Methodologies and Techniques in the Industrial Engineering Using Text Mining

  • 조근호 (한양대학교 산업경영공학과) ;
  • 임시영 (한양대학교 산업경영공학과) ;
  • 허선 (한양대학교 산업경영공학과)
  • Cho, Geun Ho (Department of Industrial and Management Engineering, Hanyang University) ;
  • Lim, Si Yeong (Department of Industrial and Management Engineering, Hanyang University) ;
  • Hur, Sun (Department of Industrial and Management Engineering, Hanyang University)
  • 투고 : 2013.12.10
  • 심사 : 2014.02.04
  • 발행 : 2014.02.15
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초록

We survey 3,857 journal articles published on the four domestic academic journals in the industrial engineering field during 1975~2012. Titles, abstracts, and keywords of the papers are searched by means of text mining technique to draw the information on the methodologies and techniques adopted in the papers, and then we aggregate and merge similar ones to obtain final 38 representative methodologies and techniques. Trends of these methodologies and techniques are studied by analyzing frequencies, clustering, and finding association rules among them. Results of the paper can shed a light to choose tools in the future education and research in the industrial engineering related area.

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참고문헌

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피인용 문헌

  1. Analyzing the Domestic Collaborative Research Network in Industrial Engineering vol.40, pp.6, 2014, https://doi.org/10.7232/JKIIE.2014.40.6.618
  2. Topic Model Analysis of Research Trend on Spatial Big Data vol.41, pp.1, 2015, https://doi.org/10.7232/JKIIE.2015.41.1.064
  3. A Text Mining Analysis for Research Trend about Information and Communication Technology in Construction Automation vol.17, pp.6, 2016, https://doi.org/10.6106/KJCEM.2016.17.6.013
  4. Trend Analysis using Topic Modeling for Simulation Studies vol.25, pp.3, 2016, https://doi.org/10.9709/JKSS.2016.25.3.107
  5. Study on the Trends of U-City and Smart City Researches using Text Mining Technology vol.22, pp.3, 2014, https://doi.org/10.7319/kogsis.2014.22.3.087