A bacterial colony algorithm for association rule mining

dc.contributor.authorda Cunha D.S.
dc.contributor.authorXavier R.S.
dc.contributor.authorde Castro L.N.
dc.date.accessioned2024-03-13T00:58:26Z
dc.date.available2024-03-13T00:58:26Z
dc.date.issued2015
dc.description.abstract© Springer International Publishing Switzerland 2015.Bacterial colonies perform a cooperative distributed exploration of the environment. This paper describes bacterial colony networks and their skills to explore resources as a tool for mining association rules in databases. The proposed algorithm is designed to maintain diverse solutions to the problem at hand, and its performance is compared to other well-known bio-inspired algorithms, including a genetic and an immune algorithm (CLONALG) and, also, to Apriori over some benchmarks from the literature.
dc.description.firstpage96
dc.description.lastpage103
dc.description.volume9375 LNCS
dc.identifier.doi10.1007/978-3-319-24834-9_12
dc.identifier.issn1611-3349
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/36268
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.subject.otherlanguageAssociation rules
dc.subject.otherlanguageBacterial colony
dc.subject.otherlanguageBio-inspired algorithm
dc.subject.otherlanguageData Mining
dc.titleA bacterial colony algorithm for association rule mining
dc.typeArtigo de evento
local.scopus.citations0
local.scopus.eid2-s2.0-84983684806
local.scopus.subjectApriori
local.scopus.subjectBacterial colonies
local.scopus.subjectBio-inspired algorithms
local.scopus.subjectCLONALG
local.scopus.subjectDistributed exploration
local.scopus.subjectDiverse solutions
local.scopus.subjectImmune algorithms
local.scopus.subjectMining associations
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84983684806&origin=inward
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