텍스트 마이닝을 통한 건설기계분야 국내 정부 R&D 연구동향 분석
Text-Mining Analysis of Korea Government R&D Trends in Construction Machinery Domains
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초록
To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: ‘equipment,’ ‘smart,’ and ‘eco-friendly.’ Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.
Abstract
To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: ‘equipment,’ ‘smart,’ and ‘eco-friendly.’ Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.
참고문헌 (25)
- Adeva, J. J. G., "Mining Text with Piminto", IEEE Internet Computing, 10(4), pp.27~35 (2006)
- "Introduction to Natural Language Processing Using Deep Learning"[URL]
- Blei, D. M., "Latent Dirichlet Allocation", Journal of Machine Learning Research, 3, pp.993~1022 (2003)
- "Centrality"[URL]
- Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS, "Chakraborty, G.", SAS Institute, ~ (2014)
- Deepak Sharma, "Trend Analysis in Machine Learning Research Using Text Mining", International Confernece on Advances in Computing, Comminication Control and Networking (ICACCCN2018) (2018)
- Gokhberg, L., "Advanced text-mining for trend analysis of Russia’s Extractive Industries", Futures, 115 (2020)
- Griffiths, T. L., "Finding scientific topics", Proceedings of the National Academy of Sciences, 101, pp.5228~5235 (2004)
- Kim, D. H., "Analysis of FinTech and Digital Financial Service Trends in the New Normal Era through Text Mining", pp.2021
- How text is analyzed, Statistics Korea, "Kim, D. H.", Statistics Training Institute, ~ (2017)
- 김형욱, "토픽 모델링을 활용한 양자역학 관련 기사 분석: LDA 모형, CTM 모형, STM 모형 결과 비교를 중심으로", 새물리, 70(5), pp.493~502 (2020), 한국물리학회[DOI]
- 김지훈, "텍스트마이닝을 활용한 농업 R&D 키워드 분석", 한국산학기술학회논문지, 22(2), pp.721~732 (2021), 한국산학기술학회[DOI]
- Kim, Y. H., "Social Network Analysis" (2016), Park Youngsa
- Kim, Y. H., "Understanding and Application of Social Network Analysis Techniques: Network Structure, Clus-tering, and QAP", Korea Institute of Public Administration, 34, pp.58~68 (2020)
- Lee, D.W., "New Horizons for the Construction Machinery Industry", Auto Journal, pp.39~42 (2021)
- 이소정, "잠재디리클레할당 분석을 이용한 ‘노인일자리’ 관련 신문기사 토픽분석", 디지털융복합연구, 18(10), pp.537~546 (2020), 한국디지털정책학회[DOI]
- 이상숙, "빅데이터 분석을 통해 본 AI교육에 대한 사회적 인식: 뉴스기사와 트위터를 중심으로", 디지털융복합연구, 18(6), pp.9~16 (2020), 한국디지털정책학회[DOI]
- Lee, Y. S., "A Study on Serviceization Research Topics Using Ontology and Text Mining", pp.2016
- 임시영, "텍스트마이닝 기법을 활용한 정보통신기술 기반 건설자동화 연구동향 분석", 한국건설관리학회 논문집, 17(6), pp.13~23 (2016), 한국건설관리학회[DOI]
- Basic Plan for Construction Technology Promotion, "Ministry of Land, Infrastructure and Transport", MOLIT, ~ (2017)
- Machine industry develop-ment plan, "Ministry of Trade Industry and Energy", MOTIE, ~ (2022)
- "Network Centrality Value – Degree, Betweenness, Eigenvector, Closeness"[URL]
- 오창석, "텍스트마이닝을 활용한 도로분야 ITS 정책이슈 탐색기법 정립", 한국ITS학회 논문지, 15(6), pp.10~23 (2016), 한국ITS학회[DOI]
- Current Status and Future Directions of the Construction Machinery Industry, "Oh, S.H.", Industry Economy, 67~74 (2023)
- 우창우, "LDA 토픽모델링을 통한 ICT분야 국가연구개발사업의 주요 연구토픽 및 동향 탐색", 한국융합학회논문지, 11(7), pp.9~18 (2020), 한국융합학회[DOI]