Mining Frequent Patterns Based on IS\++-Tree Model

IS-tree is a novel mathematical model presented recently, which has been success fully applied to full-text index and storage in text database. In this paper, it s application is extended to data mining and an algorithm is presented for minin g frequent patterns based on IS\++-tree. The algorithm builds frequent patterns directly, as FP-growth algorithm does. However, it has several advantages over t he FP-tree model. Firstly, it scans the transaction database only once. Secondly , the mining process is only associated with one root tree. Thirdly, IS\++-tree can be dynamically updated by increments. The performance study shows that the a lgorithm efficiency is equal to or even higher than FP-growth. Above all, IS\++- tree is a good model to index transaction database, and it can support query on transactions with high efficiency.