Exploration of continuous sequential patterns using the CPGrowth algorithm

In the following paper we present the UCP-Tree and a new algorithm called CPGrowth for continuous pattern mining. The UCP-Tree is an aggregation tree that stores common subsequences of input sequences in the same nodes. The characteristic feature of the CPGrowth algorithm is that it does not require transitional trees at the next recursion levels. Moreover, new sequences can be inserted into the UPC-Tree without rebuilding, which is a considerable advantage considering that Trajectory Data Warehouses store massive amounts of data. In this paper we compared the efficiency of the proposed index with one of the fastest continuous pattern mining algorithms.