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1、MachLearn(2011)82:142DOI10.1007/s10994-010-5216-5Editorialsurvey:swarmintelligencefordataminingDavidMartens·BartBaesens·TomFawcettReceived:22April2010/Revised:24August2010/Accepted:25August2010/Publishedonline:17September2010©TheAuthor(s)2010AbstractThispapersurvey
2、stheintersectionoftwofascinatingandincreasinglypopulardomains:swarmintelligenceanddatamining.Whereasdatamininghasbeenapopularacademictopicfordecades,swarmintelligenceisarelativelynewsubfieldofartificialin-telligencewhichstudiestheemergentcollectiveintelligenceofgroup
3、sofsimpleagents.Itisbasedonsocialbehaviorthatcanbeobservedinnature,suchasantcolonies,flocksofbirds,fishschoolsandbeehives,whereanumberofindividualswithlimitedcapabilitiesareabletocometointelligentsolutionsforcomplexproblems.Inrecentyearstheswarmintelligenceparadigmha
4、sreceivedwidespreadattentioninresearch,mainlyasAntColonyOptimization(ACO)andParticleSwarmOptimization(PSO).Thesearealsothemostpop-ularswarmintelligencemetaheuristicsfordatamining.Inadditiontoanoverviewofthesenatureinspiredcomputingmethodologies,wediscusspopulardata
5、miningtechniquesbasedontheseprinciplesandschematicallylistthemaindifferencesinourliteraturetables.Fur-ther,weprovideaunifyingframeworkthatcategorizestheswarmintelligencebaseddataminingalgorithmsintotwoapproaches:effectivesearchanddataorganizing.Finally,welistintere
6、stingissuesforfutureresearch,herebyidentifyingmethodologicalgapsincur-rentresearchaswellasmappingopportunitiesprovidedbyswarmintelligencetocurrentchallengeswithindataminingresearch.Editor:FosterProvost.D.MartensDepartmentofBusinessAdministrationandPublicManagement,
7、UniversityCollegeGhent,GhentUniversity,Ghent,BelgiumD.Martens()·B.BaesensDepartmentofDecisionSciences&InformationManagement,K.U.Leuven,Leuven,Belgiume-mail:David.Martens@econ.kuleuven.beB.BaesensSchoolofManagement,UniversityofSouthampton,Southampton,UKT.FawcettPro
8、ofpoint,Inc.,Sunnyvale,CA,USA2MachLearn(2011)82:142KeywordsSwarmintelligence·Antcolonyoptimization·Particleswarmoptimization·Datamining1Introduct
