텍스트 마이닝을 통한 건설기계분야 국내 정부 R&D 연구동향 분석

서지정보

ㆍ발행기관 : 한국산업경영시스템학회 ㆍ수록지정보 : 산업경영시스템학회지 / 46권 / 4호
ㆍ저자명 : 윤봄, 배준수

목차

1. 서 론
2. 이론적 배경 및 선행연구
2.1 텍스트 마이닝
2.2 동향분석 선행연구 사례
3. 데이터 분석방법
3.1 데이터 수집 및 전처리
3.2 키워드 빈도분석
3.3 N-gram 분석
3.4 토픽모델링 분석
4. 연구 결과
4.1 키워드 빈도 분석
4.2 N-gram 분석
4.3 토픽모델링 분석
5. 결 론

영어 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.

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