Application of data-mining to state transportation agencies projects databases
Year: 2007
Type: article
Abstract: Data mining is a relatively new data analysis technique that has the ability to discover patterns stored within historical data and is now considered a catalyst for enhancing business processes by avoiding failure patterns and exploiting success patterns. This technique is widely used in business applications including market segmentation, fraud detection, and credit risk analysis as well as many other applications. In the construction domain however, the use of data mining has been extremely limited. Data mining usually requires the availability of a large database of previous cases to be analyzed. Therefore applications in the construction industry must be geared to those situations where such databases are readily available. This paper describes a research effort to explore a potential use of data mining in the construction industry. Real data about asphalt paving projects was collected from various IDOT (Illinois Department of Transportation) sources and analyzed using data mining techniques. The results indicate that data mining can provide information beyond the use of general statistical analysis. Various rules and patterns were derived from the original database, which could be applied to support decision-making. The limitations of data mining are also noted including the need to verify and test the discovered patterns.
Author: Khaled Nassar
Institution: University of Sharjah
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W372929718