Abstract
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.
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Tanbeer, S.K., Ahmed, C.F., Jeong, BS., Lee, YK. (2008). CP-Tree: A Tree Structure for Single-Pass Frequent Pattern Mining. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2008. Lecture Notes in Computer Science(), vol 5012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68125-0_108
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DOI: https://doi.org/10.1007/978-3-540-68125-0_108
Publisher Name: Springer, Berlin, Heidelberg
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