A Natural Language Processing-Based Approach for Clustering Construction Projects
Publication: Construction Research Congress 2022
ABSTRACT
Many construction project owners group their projects into different work types to facilitate effective project management decisions. This categorization significantly helps owner agencies narrow down and analyze the historical projects of a similar type to extract meaningful patterns that can support various project management decisions. However, many owners, particularly state highway agencies, typically rely on project engineers’ subjective judgments to classify a new project or do not even have systematic project classification criteria. In addition, many projects are a mixture of work types with varying proportions. A systematic and objective process of classifying projects is desirable to generate a more accurate and less disputable categorization of projects, thereby improving project management decision-making. This study proposes a natural language processing-based model for grouping projects with similar work components and portions into the same group. For a specific project, work items’ descriptions and cost composition are the key input variables of the model. Bid tabulation data from a highway agency were collected and used for model development and evaluation.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
AASHTO. (2013). Practical guide to cost estimating. AASHTO Washington, DC.
Cao, Y., Ashuri, B., and Baek, M. (2018). “Prediction of Unit Price Bids of Resurfacing Highway Projects through Ensemble Machine Learning.” Journal of Computing in Civil Engineering, 32(5).
Carrillo, P. (2005). “Lessons learned practices in the engineering, procurement and construction sector.” Engineering, construction and architectural management, 12(3), 236–250.
Cirilovic, J., Vajdic, N., Mladenovic, G., and Queiroz, C. (2014). “Developing Cost Estimation Models for Road Rehabilitation and Reconstruction: Case Study of Projects in Europe and Central Asia.” Journal of Construction Engineering and Management, 140(3), 04013065.
CTDOT (Connecticut Department of Transportation). (2019). Connecticut Department of Transportation 2019 Estimating Guidelines. Connecticut Department of Transportation.
ITD (Idaho Transportation Department). (2020). Construction Cost Estimating Guide. Idaho Transportation Department.
Jeong, H. D., Le, C., and Devaguptapu, V. (2019). Effective Production Rate Estimation Using Construction Daily Work Report Data. Montana. Dept. of Transportation. Research Programs.
Karaca, I., Gransberg, D. D., and Jeong, H. D. (2020). “Improving the Accuracy of Early Cost Estimates on Transportation Infrastructure Projects.” Journal of Management in Engineering, 36(5).
Le, C., Jeong, H. D., Le, T., and Kang, Y. (2020). “Evaluating Contractors’ Production Performance in Highway Projects Using Historical Daily Work Report Data.” Journal of Management in Engineering, 36(3), 04020015.
Le, C., Shrestha, K. J., Jeong, H. D., and Damnjanovic, I. (2021a). “A sequential pattern mining driven framework for developing construction logic knowledge bases.” Automation in Construction, 121, 103439.
Le, C., Yaw, M. W., Jeong, H. D., and Choi, K. (2021b). “Comprehensive Evaluation of Influential Factors on Public Roadway Project Contract Time.” Journal of Management in Engineering, 37(5), 04021044.
MDT (Montana Department of Transportation). (2016). Cost Estimation Procedure for Highway Design Projects. Montana Department of Transportation.
PennDOT (Pennsylvania Department of Transportation). (2018). Estimating Manual. Pennsylvania Department of Transportation.
Qiao, Y., Fricker, J. D., and Labi, S. (2019). “Quantifying the Similarity between Different Project Types Based on Their Pay Item Compositions: Application to Bundling.” Journal of Construction Engineering and Management, 145(9), 04019053.
Shehab, T., and Meisami-Fard, I. (2013). “Cost-Estimating Model for Rubberized Asphalt Pavement Rehabilitation Projects.” Journal of Infrastructure Systems, 19(4), 496–502.
Shrestha, K. J., Le, C., Jeong, H. D., and Le, T. “Mining Daily Work Report Data for Detecting Patterns of Construction Sequences.” Proc., Creative Construction Conference 2019, 578–583.
Taylor, T. R., Goodrum, P. M., Brockman, M., Bishop, B., Shan, Y., Sturgill, R. E., and Hout, K. (2013). “Updating the Kentucky Contract Time Determination System.”
Taylor, T. R. B., Sturgill, R. E., and Li, Y. (2017). Practices for Establishing Contract Completion Dates for Highway Projects.
TxDOT (Texas Department of Transportation). (n.d.). Risk-Based Construction Cost Estimating - Reference Guide. Texas Department of Transportation.
WSDOT (Washington State Department of Transportation). (2015). Cost Estimating Manual for Projects. Washington State Department of Transportation.
Information & Authors
Information
Published In
History
Published online: Mar 7, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.