Efficiently mining closed constrained frequent ordered subtrees by using border information

Authors:
Tomonobu Ozaki;Takenao Ohkawa
Affiliations:
Graduate School of Science and Technology, Kobe University, Kobe, Japan;Graduate School of Science and Technology, Kobe University, Kobe, Japan
Venue:
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2007

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Abstract

In this paper, in order to alleviate the problem that frequent subtree miners often discover huge number of patterns, we propose two algorithms for discovering closed ordered subtrees under anti-monotone constraints about the structure of patterns. The proposed algorithms discover closed constrained subtrees by utilizing the pruning based on the occurrence matching and border patterns effectively. Experimental results show the effectiveness of the proposed algorithms.