Paper title: |
Pre-Bid Clarification for Construction Project Risk Identification Using Unstructured Text Data Analysis |
Authors: |
Jeehee Lee, June-Seong Yi, Jeongwook Son and Ye-Eun Jang |
Summary: |
This paper analysed construction bidding information in order to define risk factors that can be appeared in the bid documents of construction projects. For this purpose, text analysis was conducted on biddersÕ inquiry information (Pre-bid RFI), which inquires uncertain information and omissions in the bid documents in order for pre-bid clarification. From the results of the analysis, what types of risk factors exist in the bid documents and what parts of the bid documents can be pre-reviewed to proactively respond to the uncertain ownerÕs requirements. The results are expected to be used as important information for pre-bid clarification of bid documents. Moreover, this study can be meaningful in that it provides a comprehensive way to grasp a large amount of 1,054 documents without analysing the contents of individual documents directly through analysis of bidding information of construction projects using text mining. |
Type: |
regular paper |
Year of publication: |
2017 |
Keywords: |
Bid Documents, Pre-Bid Clarification, BiddersÕ Inquiries, Text Mining |
Series: |
jc3:2017 |
Download paper: |
/pdfs/LC3_2017_paper_028.pdf |
Citation: |
Jeehee Lee, June-Seong Yi, Jeongwook Son and Ye-Eun Jang (2017).
Pre-Bid Clarification for Construction Project Risk Identification Using Unstructured Text Data Analysis. Lean and Computing in Construction Congress (LC3): Volume I Ð Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 219-227,
http://itc.scix.net/paper/lc3-2017-028
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