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10.1109/ICDM.2006.10guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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AC-Close: Efficiently Mining Approximate Closed Itemsets by Core Pattern Recovery

Published: 18 December 2006 Publication History

Abstract

Recent studies have proposed methods to discover approximate frequent itemsets in the presence of random noise. By relaxing the rigid requirement of exact frequent pattern mining, some interesting patterns, which would previously be fragmented by exact pattern mining methods due to the random noise or measurement error, are successfully recovered. Unfortunately, a large number of "uninteresting" candidates are explored as well during the mining process, as a result of the relaxed pattern mining methodology. This severely slows down the mining process. Even worse, it is hard for an end user to distinguish the recovered interesting patterns from these uninteresting ones. In this paper, we propose an efficient algorithm AC-Close to recover the approximate closed itemsets from "core patterns". By focusing on the so-called core patterns, integrated with a top-down mining and several effective pruning strategies, the algorithm narrows down the search space to those potentially interesting ones. Experimental results show that AC-Close substantially outperforms the previously proposed method in terms of efficiency, while delivers a similar set of interesting recovered patterns.

Cited By

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  • (2019)Exploring Frequented Regions in Pan-Genomic GraphsIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2018.286456416:5(1424-1435)Online publication date: 1-Sep-2019
  • (2018)Mining top-k approximate closed patterns in an imprecise databaseInternational Journal of Grid and Utility Computing10.1504/IJGUC.2018.0916969:2(97-107)Online publication date: 1-Jan-2018
  • (2017)Exploring Frequented Regions in Pan-Genomic GraphsProceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics10.1145/3107411.3107427(89-97)Online publication date: 20-Aug-2017
  • Show More Cited By

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Published In

cover image Guide Proceedings
ICDM '06: Proceedings of the Sixth International Conference on Data Mining
December 2006
1209 pages
ISBN:0769527019

Publisher

IEEE Computer Society

United States

Publication History

Published: 18 December 2006

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Cited By

View all
  • (2019)Exploring Frequented Regions in Pan-Genomic GraphsIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2018.286456416:5(1424-1435)Online publication date: 1-Sep-2019
  • (2018)Mining top-k approximate closed patterns in an imprecise databaseInternational Journal of Grid and Utility Computing10.1504/IJGUC.2018.0916969:2(97-107)Online publication date: 1-Jan-2018
  • (2017)Exploring Frequented Regions in Pan-Genomic GraphsProceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics10.1145/3107411.3107427(89-97)Online publication date: 20-Aug-2017
  • (2014)Finding Robust Itemsets under SubsamplingACM Transactions on Database Systems10.1145/265626139:3(1-27)Online publication date: 7-Oct-2014
  • (2012)Application-independent feature construction based on almost-closedness propertiesKnowledge and Information Systems10.5555/3225656.322593330:1(87-111)Online publication date: 1-Jan-2012
  • (2010)CloseVizProceedings of the ACM SIGKDD Workshop on Useful Patterns10.1145/1816112.1816116(17-26)Online publication date: 25-Jul-2010
  • (2010)A generative pattern model for mining binary datasetsProceedings of the 2010 ACM Symposium on Applied Computing10.1145/1774088.1774320(1109-1110)Online publication date: 22-Mar-2010
  • (2009)Emerging CubesInformation Systems10.1016/j.is.2009.03.00134:6(536-550)Online publication date: 1-Sep-2009
  • (2008)Actionability and formal conceptsProceedings of the 6th international conference on Formal concept analysis10.5555/1787746.1787748(14-31)Online publication date: 25-Feb-2008
  • (2008)Quantitative evaluation of approximate frequent pattern mining algorithmsProceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1401890.1401930(301-309)Online publication date: 24-Aug-2008
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