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Erschienen in:
2008 | OriginalPaper | Buchkapitel
CP-Tree: A Tree Structure for Single-Pass Frequent Pattern Mining
verfasst von : Syed Khairuzzaman Tanbeer, Chowdhury Farhan Ahmed, Byeong-Soo Jeong, Young-Koo Lee
Erschienen in: Advances in Knowledge Discovery and Data Mining
Verlag: Springer Berlin Heidelberg
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FP-growth algorithm using FP-tree has been widely studied for frequent pattern mining because it can give a great performance improvement compared to the candidate generation-and-test paradigm of
Apriori
. However, it still requires two database scans which are not applicable to processing data streams. In this paper, we present a novel tree structure, called CP-tree (Compact Pattern tree), that captures database information with one scan (
Insertion phase
) and provides the same mining performance as the FP-growth method (
Restructuring phase
) by dynamic tree restructuring process. Moreover, CP-tree can give full functionalities for interactive and incremental mining. Extensive experimental results show that the CP-tree is efficient for frequent pattern mining, interactive, and incremental mining with single database scan.