On Exploring the Power-Law Relationship in the Itemset Support Distribution | Zendy

Kun-Ta Chuang | Zendy; JiunLong Huang | Zendy; Ming-Syan Chen⋆ | Zendy

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On Exploring the Power-Law Relationship in the Itemset Support Distribution

Author(s) -

Kun-Ta Chuang,

JiunLong Huang,

Ming-Syan Chen⋆

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-32960-9

DOI - 10.1007/11687238_41

Subject(s) - computer science , data mining , distribution (mathematics) , explosive material , power (physics) , power law , theoretical computer science , mathematics , statistics , organic chemistry , quantum mechanics , mathematical analysis , chemistry , physics

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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