Evolutionary and immune algorithms applied to association rule mining

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dc.contributor.authorDa Cunha D.S.
dc.contributor.authorDe Castro L.N.
dc.date.accessioned2024-03-13T01:06:29Z
dc.date.available2024-03-13T01:06:29Z
dc.date.issued2012
dc.description.abstractAssociation rule mining is one of the most important data mining tasks. It corresponds to the determination of rules that associate items to other items in a data set, where the items are attributes in transactional databases. Although evolutionary algorithms have been used in this task for some time, there are few applications of immune algorithms to such problem. This paper presents one typical genetic algorithm plus two clonal selection algorithms applied to association rule mining under the perspective of several measures of interest. © 2012 Springer-Verlag.
dc.description.firstpage628
dc.description.lastpage635
dc.description.volume7677 LNCS
dc.identifier.doi10.1007/978-3-642-35380-2_73
dc.identifier.issn0302-9743
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/36718
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.subject.otherlanguageArtificial Immune Systems
dc.subject.otherlanguageAssociation Rule Mining
dc.subject.otherlanguageData Mining
dc.subject.otherlanguageEvolutionary Algorithms
dc.titleEvolutionary and immune algorithms applied to association rule mining
dc.typeArtigo de evento
local.scopus.citations2
local.scopus.eid2-s2.0-84871593005
local.scopus.subjectArtificial Immune System
local.scopus.subjectClonal selection algorithms
local.scopus.subjectData mining tasks
local.scopus.subjectData sets
local.scopus.subjectImmune algorithms
local.scopus.subjectTransactional database
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84871593005&origin=inward
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