On exploring the power-law relationship in the itemset support distribution

Kun Ta Chuang, Jiun Long Huang, Ming Syan Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Database Technology - EDBT 2006 - 10th International Conference on Extending Database Technology, Proceedings
Pages682-699
Number of pages18
DOIs
Publication statusPublished - 2006
Event10th International Conference on Extending Database Technology, EDBT 2006 - Munich, Germany
Duration: 2006 Mar 262006 Mar 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3896 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Conference on Extending Database Technology, EDBT 2006
Country/TerritoryGermany
CityMunich
Period06-03-2606-03-31

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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