A Novel Tree Cluster Approach Based on Least Closed Tree
Xin Yu Guo, Yun Li, Yunhao Yuan, Jia Xin Wu, Ling Chen · 2009
The extensive application of tree model has made tree mining become a hot field in data mining research. As an important branch of tree mining, tree cluster plays a fundamental analysis role in many areas. In this paper, a tree cluster algorithm was proposed based on least closed tree, which effectively solved problems in large amount of data in practical application. The basic method is bringing forward least closed tree as the candidate cluster feature, using dynamic threshold by similarity cluster to make tree cluster operation be more quick and accurate. Experimental results show that the method has higher speed and efficiency than that of other similar ones especially when large number of tree nodes.