Incremental mining of frequent patterns without candidate generation or support constraint

In this paper, we propose a novel data structure called CATS Tree. CATS Tree extends the idea of FPTree to improve storage compression and allow frequent pattern mining without generation of candidate item sets. The proposed algorithms enable frequent pattern mining with different supports without rebuilding the tree structure. Furthermore, the algorithms allow mining with a single pass over the database as well as efficient insertion or deletion of transactions at any time.