A new closed frequent items mining from tree data

Mining the frequent sub-patterns from tree dataset is a hot research topic, and a lot of research work has done on the frequent item field. Mining frequent item sets is a key step in many data mining problems, such as association rule mining, sequential pattern mining, classification, and so on. This paper proposed a data model named TTDOM to record the history changing process. TTDOM utilize two additional time tags ("ins" and "del") describe the changes of each node of tree data. Then, an algorithm is proposed to discover all the sub-trees in the TTDOM dataset. Finally, we use bitmap method to close the mining result. The experiment result shows that our approach is efficient.