Association rule mining using a bacterial colony algorithm

Página do item simplificado
dc.contributor.authorDa Cunha D.S.
dc.contributor.authorXavier R.S.
dc.contributor.authorFerrari D.G.
dc.contributor.authorDe Castro L.N.
dc.date.accessioned2024-03-13T00:53:37Z
dc.date.available2024-03-13T00:53:37Z
dc.date.issued2016
dc.description.abstract© 2015 IEEE.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.identifier.doi10.1109/LA-CCI.2015.7435950
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/35995
dc.relation.ispartof2015 Latin-America Congress on Computational Intelligence, LA-CCI 2015
dc.rightsAcesso Restrito
dc.subject.otherlanguageassociation rules
dc.subject.otherlanguagebacterial colony
dc.subject.otherlanguagebio-inspired algorithm
dc.subject.otherlanguagedata mining
dc.titleAssociation rule mining using a bacterial colony algorithm
dc.typeArtigo de evento
local.scopus.citations3
local.scopus.eid2-s2.0-84969594352
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=84969594352&origin=inward
Arquivos
Coleções
Artigo de evento