Abstract
Based on the FP-tree data structure, this paper presents an efficient algorithm for mining the complete set of positive correlated item pairs. Our experimental results on both synthetic and real world datasets show that, the performance of our algorithm is significantly better than that of the previously developed Taper algorithm over practical ranges of correlation threshold specifications.
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He, Z., Deng, S., Xu, X. (2005). An FP-Tree Based Approach for Mining All Strongly Correlated Item Pairs. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_108
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DOI: https://doi.org/10.1007/11596448_108
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30818-8
Online ISBN: 978-3-540-31599-5
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