Abstract
Frequent embedded subtree pattern mining is an important data mining problem with broad applications. In this paper, we propose a novel embedded subtree mining algorithm, called PrefixTreeESpan (i.e. Prefix-Tree-projected Embedded-Subtree pattern), which finds a subtree pattern by growing a frequent prefix-tree. Thus, using divide and conquer, mining local length-1 frequent subtree patterns in Prefix-Tree-Projected database recursively will lead to the complete set of frequent patterns. Different fromChopper and XSpanner [4], PrefixTreeESpan does not need a checking process. Our performance study shows that PrefixTreeESpan outperforms Apriori-like algorithm: TreeMiner [6], and pattern-growth algorithms :Chopper , XSpanner .
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© 2006 Springer-Verlag Berlin Heidelberg
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Zou, L., Lu, Y., Zhang, H., Hu, R. (2006). PrefixTreeESpan: A Pattern Growth Algorithm for Mining Embedded Subtrees. In: Aberer, K., Peng, Z., Rundensteiner, E.A., Zhang, Y., Li, X. (eds) Web Information Systems – WISE 2006. WISE 2006. Lecture Notes in Computer Science, vol 4255. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11912873_51
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DOI: https://doi.org/10.1007/11912873_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48105-8
Online ISBN: 978-3-540-48107-2
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