TY - GEN
T1 - On exploring the power-law relationship in the itemset support distribution
AU - Chuang, Kun Ta
AU - Huang, Jiun Long
AU - Chen, Ming Syan
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2006
Y1 - 2006
N2 - We identify and explore in this paper an important phenomenon which points out that the power-law relationship appears in the distribution of itemset supports. Characterizing such a relationship will benefit many applications such as providing the direction of tuning the performance of the frequent-itemset mining. Nevertheless, due to the explosive number of itemsets, it will be prohibitively expensive to retrieve characteristics of the power-law relationship in the distribution of itemset supports. As such, we also propose in this paper a valid and cost-effective algorithm, called algorithm PPL, to extract characteristics of the distribution without the need of discovering all itemsets in advance. Experimental results demonstrate that algorithm PPL is able to efficiently extract the characteristics of the power-law relationship with high accuracy.
AB - We identify and explore in this paper an important phenomenon which points out that the power-law relationship appears in the distribution of itemset supports. Characterizing such a relationship will benefit many applications such as providing the direction of tuning the performance of the frequent-itemset mining. Nevertheless, due to the explosive number of itemsets, it will be prohibitively expensive to retrieve characteristics of the power-law relationship in the distribution of itemset supports. As such, we also propose in this paper a valid and cost-effective algorithm, called algorithm PPL, to extract characteristics of the distribution without the need of discovering all itemsets in advance. Experimental results demonstrate that algorithm PPL is able to efficiently extract the characteristics of the power-law relationship with high accuracy.
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U2 - 10.1007/11687238_41
DO - 10.1007/11687238_41
M3 - Conference contribution
AN - SCOPUS:33745598143
SN - 3540329609
SN - 9783540329602
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 682
EP - 699
BT - Advances in Database Technology - EDBT 2006 - 10th International Conference on Extending Database Technology, Proceedings
T2 - 10th International Conference on Extending Database Technology, EDBT 2006
Y2 - 26 March 2006 through 31 March 2006
ER -