Computational & Technology Resources
an online resource for computational,
engineering & technology publications
Civil-Comp Proceedings
ISSN 1759-3433
CCP: 102
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING COMPUTING
Edited by:
Paper 158

Construction Project Cost Prediction using Text and Data Mining

T.P. Williams and J. Gong

Department of Civil and Environmental Engineering
Rutgers University, New Brunswick, United States of America

Full Bibliographic Reference for this paper
T.P. Williams, J. Gong, "Construction Project Cost Prediction using Text and Data Mining", in , (Editors), "Proceedings of the Fourteenth International Conference on Civil, Structural and Environmental Engineering Computing", Civil-Comp Press, Stirlingshire, UK, Paper 158, 2013. doi:10.4203/ccp.102.158
Keywords: construction costs, data mining, text mining.

Summary
In this paper, text data from a sample of competitively bid California highway projects has been used to predict the likely level of cost overrun in construction projects. A text description of the project and the text of the five largest project line items were used as input. The text data were converted to numerical attributes using text-mining algorithms and singular value decomposition. Classification rules were produced using the Ridor (ripple down rules) classification algorithm. Results of the modeling effort showed that the text data could be used to gain insight into the likely level of project cost overrun.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £65 +P&P)