Analyzing Asset Management Data Using Data and Text Mining

Williams, Trefor; Halling, Marv; Rutgers University. Department of Civil & Environmental Engineering

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Analyzing Asset Management Data Using Data and Text Mining

2014-07-01
By Williams, Trefor ; Halling, Marv

[PDF-475.62 KB]

English

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Details:

Creators:

Williams, Trefor ; Halling, Marv

Williams, Trefor ; Halling, Marv Less -
Corporate Creators:

Rutgers University. Department of Civil & Environmental Engineering
Corporate Contributors:

United States. Dept. of Transportation. Research and Innovative Technology Administration
Subject/TRT Terms:

[+]

Algorithms Asset Management Construction Construction Projects Costs Data Analysis Data And Information Technology Data Mining Finance Highways I10: Economics And Administration I50: Construction And Supervision Of Construction Mathematical Prediction Research Hub Text Mining
Publication/ Report Number:

CAIT-UTC-031
Resource Type:

Tech Report
Geographical Coverage:

California ; United States

California ; United States Less -
TRIS Online Accession Number:

01570305
Edition:

Final Report
Corporate Publisher:

Rutgers University. Center for Advanced Infrastructure and Transportation
Abstract:

Predictive models using text from a sample competitively bid California highway projects have been used to predict a construction projects likely level of cost overrun. 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. Two models were produced. The first used only the text description as input, while the second combined the text data with the numeric value of the low bid. Classification models were produced using the K-Star classification algorithm. Modeling results indicated information in the textual descriptions is related to the projects level of cost overrun.
Format:

PDF
Funding:

DTRT12-G-UTC16
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:41c8096d32e7ec4a6f33c614d87da1d0a3fe7f0feb940f5cb986ca3b4fca6eaf
Download URL:

https://rosap.ntl.bts.gov/view/dot/28672/dot_28672_DS1.pdf
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No Additional Files

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Analyzing Asset Management Data Using Data and Text Mining

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