Discovery of Useful Patterns in Intelligent Transportation Systems Data

Data mining, which is the process of nding useful patterns in large collections of data, is emerging as an important area of research that has been successfully applied to many domains. This research develops an application of data mining techniques to data collected for intelligent transportation systems (ITS). In order to identify a set of primitives for mining over ITS data, an implementation was developed of the \Apriori" algorithm for nding association rules in large data sets. It is hoped that experimentation with this implementation and other tools will lead to an understanding of some of the primitives appropriate for this data mining task.