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KSCE Journal of Civil Engineering

, Volume 22, Issue 4, pp 1027–1039 | Cite as

Association Rules Mined from Construction Accident Data

  • Dong-Pil Shin
  • Young-Jun Park
  • Jongwon Seo
  • Dong-Eun Lee
Construction Management
  • 114 Downloads

Abstract

Worker safety awareness issue in construction job site is a major concern due to the hazardous work conditions attributed to the dynamic and complex nature of construction job sites. Providing intuitive knowledge expressed as linguistic statements would be useful for corrective and/or preventive actions. This study investigates 98,189 serious injury and fatal accidents that occurred in Korean building construction sites in the period 2006–2010 in order to discover intuitive knowledge expressed as association rules among multi-attributes of construction accidents. 74 association rules are identified as valid by computing the minimum support, confidence, and lift of each rule. Finally, 30 consolidated association rules are obtained as meaningful knowledge for implementing corrective and preventive actions for effective job site safety management after either combining or pruning those 74 rules. This study provides the theoretical rule base that defines the association among accident attributes causing serious injuries and fatalities at construction job site. These rules may be useful for efficient safety control and education.

Keywords

fatality serious injury association rule data mining construction accident 

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Copyright information

© Korean Society of Civil Engineers 2018

Authors and Affiliations

  • Dong-Pil Shin
    • 1
  • Young-Jun Park
    • 1
  • Jongwon Seo
    • 2
  • Dong-Eun Lee
    • 1
  1. 1.School of Architecture and Civil EngineeringKyungpook National UniversityDaeguKorea
  2. 2.Dept. of Civil and Environmental EngineeringHanyang UniversitySeoulKorea

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