By analyzing the existing prefix-tree data structure, an improved pattern tree was introduced for processing new transactions. It firstly stored transactions in a lexicographic order tree and then restructured the tree by sorting each path in a frequency-descending order. While updating the improved pattern tree, there was no need to rescan the entire new database or reconstruct a new tree for incremental updating. A test was performed on synthetic dataset T1014D100K with 100 000 transactions and 870 items. Experimental results show that the smaller the minimum sup- port threshold, the faster the improved pattern tree achieves over CanTree for all datasets. As the minimum support threshold increased from 2% to 3.5%, the runtime decreased from 452.71 s to 186.26 s. Meanwhile, the runtime re- quired by CanTree decreased from 1 367.03 s to 432.19 s. When the database was updated, the execution time of im- proved pattern tree consisted of construction of original improved pattern trees and reconstruction of initial tree. The experiment results showed that the runtime was saved by about 15% compared with that of CanTree. As the number of transactions increased, the runtime of improved pattern tree was about 25% shorter than that of FP-tree. The improved pattern tree also required less memory than CanTree.
