| Title |
Analysis of Potential Construction Risk Types in Formal Documents Using Text Mining |
| Authors |
엄세호(Eom, Sae Ho) ; 차기춘(Cha, Gichun) ; 박선규(Park, Sun Kyu) ; 박승희(Park, Seunghee) ; 박종호(Park, Jongho) |
| DOI |
https://doi.org/10.12652/Ksce.2023.43.1.0091 |
| Keywords |
텍스트 마이닝; 군집분석; Word2Vec; 잠재 리스크; 공문 Text mining; Cluster analysis; Word2Vec; Potential risk; Formal document |
| Abstract |
Since risks occurring in construction projects can have a significant impact on schedules and costs, there have been many studies onthis topic. However, risk analysis is often limited to only certain construction situations,and experience-dependent decision-making istherefore mainly performed. Data-based analyses have only been partially applied to safety and contract documents. Therefore, in thisstudy, cluster analysis and a Word2Vec algorithm were applied to formal documents that contain important elements for contractorsor clients. An initial classification of document content into six types was performed through cluster analysis, and 157 occurrence typeswere subdivided through application of the Word2Vec algorithm. The derived terms were re-classified into five categories and reviewedas to whether the terms could develop into potential construction risk factors. Identifying potential construction risk factors will behelpful as basic data for process management in the construction industry |