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      텍스트마이닝(Text Mining) 기법을 이용한 건설안전 사고발생 유형분석 및 대책 수립에 관한 연구 = Analysis of Construction Accident Occurrence Type and Establishment of Countermeasures Using Text Mining Technique

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      https://www.riss.kr/link?id=T16144877

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Objectives : Korean government aims to achieve the reduction of more than half (60% or more) of industrial accident casualties by 2022.
      For that, it is essential to prevent accidents at construction fields, which account for more than 50% of all industrial accidents.
      By adopting big data technology to analyze past industrial accident cases and establishing safety measures,
      construction safety accidents can be drastically reduced.
      In this study, using text-mining technique, disaster causes are analyzed in various ways and safety measures are established.
      Methods : As of 2020, the Korea Land & Housing corporation accounts for 30% of the total construction orders for public purposes in Korea (9.1trillion Korean won in 2020).
      The author analyzed the construction safety accidents using text-mining technique, one of big data analysis techniques, for statistical data (1,305 cases) of accidents that occurred from 2016 to 2020.
      Results and discussion : The author discusses the safety measures for type of accidents; scaffolding, formwork, and tower cranes that are concerned about large-scale accidents(disasters), and for 20 risky works of 7 types including falling, crushing/overturning, suffocation, collapsing, bumping, cutting, and stabbing.
      Conclusions : The recently enacted Severe Accident Punishment Act and the amended Occupational Safety and Health Act focus on punishing perpetrators rather than preventative measures.
      Accident cannot be prevented by punishment alone. It is appropriate to establish all safety policies focusing
      on preventive measures rather than punishment.
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      Objectives : Korean government aims to achieve the reduction of more than half (60% or more) of industrial accident casualties by 2022. For that, it is essential to prevent accidents at construction fields, which account for more than 50% of all indus...

      Objectives : Korean government aims to achieve the reduction of more than half (60% or more) of industrial accident casualties by 2022.
      For that, it is essential to prevent accidents at construction fields, which account for more than 50% of all industrial accidents.
      By adopting big data technology to analyze past industrial accident cases and establishing safety measures,
      construction safety accidents can be drastically reduced.
      In this study, using text-mining technique, disaster causes are analyzed in various ways and safety measures are established.
      Methods : As of 2020, the Korea Land & Housing corporation accounts for 30% of the total construction orders for public purposes in Korea (9.1trillion Korean won in 2020).
      The author analyzed the construction safety accidents using text-mining technique, one of big data analysis techniques, for statistical data (1,305 cases) of accidents that occurred from 2016 to 2020.
      Results and discussion : The author discusses the safety measures for type of accidents; scaffolding, formwork, and tower cranes that are concerned about large-scale accidents(disasters), and for 20 risky works of 7 types including falling, crushing/overturning, suffocation, collapsing, bumping, cutting, and stabbing.
      Conclusions : The recently enacted Severe Accident Punishment Act and the amended Occupational Safety and Health Act focus on punishing perpetrators rather than preventative measures.
      Accident cannot be prevented by punishment alone. It is appropriate to establish all safety policies focusing
      on preventive measures rather than punishment.

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      목차 (Table of Contents)

      • Ⅰ. 서 론 1
      • 1. 연구 배경 1
      • 2. 연구 목적 3
      • 3. 연구 내용 5
      • Ⅱ. 이론적 배경 및 선행연구 조사 6
      • Ⅰ. 서 론 1
      • 1. 연구 배경 1
      • 2. 연구 목적 3
      • 3. 연구 내용 5
      • Ⅱ. 이론적 배경 및 선행연구 조사 6
      • 1. 텍스트마이닝 6
      • 2. 텍스트마이닝 적용사례 7
      • Ⅲ. 연구 방법 9
      • 1. 자료 취득 9
      • 2. 빅데이터 분석 솔루션 9
      • Ⅳ. 분석결과 11
      • 1. 사고통계 분석 사망자와 재해자 수 기준 11
      • 2. 사고유형별 재해분석 현황 13
      • 3. 기간별(요일별, 월별, 분기별, 계절별) 재해분석 현황 14
      • 4. 사고원인별 재해분석 현황 17
      • 5. 공종별 재해분석 현황 18
      • 6. 지역별 재해분석 현황 20
      • 7. 공사 규모별 재해분석 현황 22
      • 8. 시공 업체별 재해분석 현황 23
      • Ⅴ. Textmining 분석에 의한 안전대책 26
      • 1. 떨어짐 사고 26
      • 2. 깔림 뒤집힘 사고 27
      • 3. 질식 사고 28
      • 4. 무너짐 사고 28
      • 5. 절단 찔림 사고 29
      • 6. 부딪힘 사고 30
      • 7. 기타 사고 30
      • Ⅵ. 결 론 32
      • 참고문헌 35
      • 참고자료 37
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