Knowledge compilation for itemset mining

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

We present a novel approach to itemset mining whereby the set of all itemsets are compiled into a compact form, closely related to binary decision diagrams. While there were previous attempts to utilize decision diagrams for storing the set of frequent itemsets this is the first approach that does not rely on backtrack search to generate such a set. Our empirical evaluation demonstrates that our approach is complementary to current approaches.

Original languageEnglish
Title of host publicationECAI 2010
PublisherIOS Press
Pages1109-1110
Number of pages2
ISBN (Print)9781607506058
DOIs
Publication statusPublished - 2010
Event2nd Workshop on Knowledge Representation for Health Care, KR4HC 2010, held in conjunction with the 19th European Conference in Artificial Intelligence, ECAI 2010 - Lisbon, Portugal
Duration: 17 Aug 201017 Aug 2010

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume215
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference2nd Workshop on Knowledge Representation for Health Care, KR4HC 2010, held in conjunction with the 19th European Conference in Artificial Intelligence, ECAI 2010
Country/TerritoryPortugal
CityLisbon
Period17/08/1017/08/10

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