한국산업경영시스템학회지 연구 주제의 토픽모델링 분석 비교

• 영문명: Topic Modeling Analysis Comparison for Research Topic in Korean Society of Industrial and Systems Engineering: Concentrated on Research Papers from 1978∼1999
• 발행기관: 한국산업경영시스템학회
• 저자명: 박동준(Dong Joon Park) 오형술(Hyung Sool Oh) 김호균(Ho Gyun Kim) 윤민(Min Yoon)
• 간행물 정보: 『산업경영시스템학회지』제44권 제4호, 113~127쪽, 전체 15쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2021.12.31

영문 초록

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applica-tions in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.

목차

Ⅰ. 서론

Ⅱ. 이론적 배경

Ⅲ. 연구 프레임워크

Ⅳ. 토픽모델링

Ⅴ. 결 론

Acknowledgements

References

키워드

Topic modeling Visualization Industrial engineering Latent Dirichlet Allocation