Zong Chunguang

Frequent simultaneously congested link-sets discovery and ranking

In the past years the number of algorithms and techniques for data mining has grown tremendously, much useful and valuable information can be obtained through data mining. With the development of the Intelligent Transportation Systems (ITS), more and more data from loops or cameras can be collected and used, which is from a good basis for the use of data mining approaches in ITS. In this paper, the frequent item-set mining algorithm is used to discover simultaneously congested link-sets in a road network. Because the amount of discovered item-sets is great, a ranking mechanism is adopted to improve the efficiency of picking the most interesting link-sets. The experiment results show that the approaches are useful for the discovering such link sets automatically and quickly.