ARM-AMO: An Efficient Association Rule Mining Algorithm Based on Animal Migration Optimization

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dc.cclicenceCC-BY-NCen
dc.contributor.authorLe Hoang, Sonen
dc.contributor.authorChiclana, Franciscoen
dc.contributor.authorKumar, Raghavendraen
dc.contributor.authorMittal, Mamtaen
dc.contributor.authorKhari, Manjuen
dc.contributor.authorChatterjee, Jyotir Moyen
dc.contributor.authorBaik, Sung Wooken
dc.date.acceptance2018-04-29en
dc.date.accessioned2018-05-15T08:52:38Z
dc.date.available2018-05-15T08:52:38Z
dc.date.issued2018-05-10
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linken
dc.description.abstractAssociation rule mining (ARM) aims to find out association rules that satisfy predefined minimum support and confidence from a given database. However, in many cases ARM generates extremely large number of association rules, which are impossible for end users to comprehend or validate, thereby limiting the usefulness of data mining results. In this paper, we propose a new mining algorithm based on Animal Migration Optimization (AMO), called ARM-AMO, to reduce the number of association rules. It is based on the idea that rules which are not of high support and unnecessary are deleted from the data. Firstly, Apriori algorithm is applied to generate frequent itemsets and association rules. Then, AMO is used to reduce the number of association rules with a new fitness function that incorporates frequent rules. It is observed from the experiments that, in comparison with the other relevant techniques, ARM-AMO greatly reduces the computational time for frequent item set generation, memory for association rule generation, and the number of rules generated.en
dc.funderN/Aen
dc.identifier.citationSon, L.H.. Chiclana, F., Kumar, R., Mittal, M., Khari, M., Chatterjee, J.M., Baik, S.W. (2018) ARM-AMO: An Efficient Association Rule Mining Algorithm Based on Animal Migration Optimization, Knowledge-Based Systems.en
dc.identifier.doihttps://doi.org/10.1016/j.knosys.2018.04.038
dc.identifier.issn0950-7051
dc.identifier.urihttp://hdl.handle.net/2086/16167
dc.language.isoen_USen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherElsevieren
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.subjectAssociation rules miningen
dc.subjectAnimal Migration Optimization (AMO)en
dc.subjectApriori algorithmen
dc.subjectParticle Swarm Optimization (PSO)en
dc.titleARM-AMO: An Efficient Association Rule Mining Algorithm Based on Animal Migration Optimizationen
dc.typeArticleen

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