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.
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References
Asai, T., et al.: Efficient Substructure Discovery from Large Semi-structured Data. In: Proc. of the 2nd Annual SIAM Symposium on Data Mining, SIAM, Philadelphia (2002)
Asai, T., et al.: Discovering Frequent Substructures in Large Unordered Trees. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds.) DS 2003. LNCS (LNAI), vol. 2843, pp. 47–61. Springer, Heidelberg (2003)
Chi, Y., et al.: Mining Closed and Maximal Frequent Subtrees from Databases of Labeled Rooted Trees. IEEE Transactions on Knowledge and Data Engineering 17(2), 190–202 (2005)
Pei, J., Han, J., Wang, W.: Mining Sequential Patterns with Constraints in Large Databases. In: Proc. of the eleventh international conference on Information and knowledge management, pp. 18–25 (2002)
Wang, C., et al.: Constraint-Based Graph Mining in Large Database. In: Zhang, Y., et al. (eds.) APWeb 2005. LNCS, vol. 3399, pp. 133–144. Springer, Heidelberg (2005)
Yan, X., Han, J.: CloseGraph: Mining Closed Frequent Graph Patterns. In: Proc. of 2003 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’03), ACM Press, New York (2003)
Zaki, M.J.: Efficiently Mining Frequent Trees in a Forest. In: Proc. of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 71–80. ACM Press, New York (2002)
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Ozaki, T., Ohkawa, T. (2007). Efficiently Mining Closed Constrained Frequent Ordered Subtrees by Using Border Information. In: Zhou, ZH., Li, H., Yang, Q. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science(), vol 4426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71701-0_81
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DOI: https://doi.org/10.1007/978-3-540-71701-0_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71700-3
Online ISBN: 978-3-540-71701-0
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