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1、PublishedinGeographicDataMiningandKnowledgeDiscovery,ResearchMonographsinGIS,TaylorandFrancis,2001.AlgorithmsandApplicationsforSpatialDataMiningMartinEster,Hans-PeterKriegel,JörgSander(UniversityofMunich)1IntroductionDuetothecomputerizationandtheadvancesinscientificdatacollectio
2、nwearefacedwithalargeandcontinuouslygrowingamountofdatawhichmakesitimpossibletointerpretallthisdatamanually.Therefore,thedevelopmentofnewtechniquesandtoolsthatsupportthehumanintrans-formingdataintousefulknowledgehasbeenthefocusoftherelativelynewandinterdisciplinaryresearcharea“k
3、nowledgediscoveryindatabases”.Knowledgediscoveryindatabases(KDD)hasbeendefinedasthenon-trivialprocessofdiscov-eringvalid,novel,potentiallyusefulandultimatelyunderstandablepatternsfromdata,apatternisanexpressioninsomelanguagedescribingasubsetofthedataoramodelapplicabletothatsubse
4、t(Fayyadetal.,1996).TheprocessofKDDisinteractiveanditerative,involvingseveralstepssuchasdataselection,datareduction,datamining,andtheevaluationofthedataminingresults.Theheartoftheprocess,however,isthedataminingstepwhichconsistsoftheapplicationofdataanal-ysisanddiscoveryalgorithm
5、sthat,underacceptablecomputationalefficiencylimitations,produceaparticularenumerationofpatternsoverthedata(Fayyadetal.,1996).Whilealotofresearchhasbeenconductedonknowledgediscoveryanddatamininginrela-tionaldatabases(seee.g.(Chenetal.,1996)or(Fayyad,1997)foranoverview),onlyafewwo
6、rksdealwithknowledgediscoveryinspatialdatabases(see(Gueting,1994)foranintroductiontospa-tialdatabases,(Koperskietal.,1996)foranoverviewofspatialdatamining).Findingimplicitreg-ularities,rulesorpatternshiddeninspatialdatabasesisanimportanttask,e.g.forgeo-marketing,trafficcontrolor
7、environmentalstudies.Aspatialdatabasecontainsobjectswhicharecharacterizedbyaspatiallocationand/orexten-sionaswellasbyseveralnon-spatialattributes.Figure7.1illustratesaspatialdatabaseonBavariaasanexample.DepictedistherelationCommunitiescontainingpolygonswhichrepresentcommu-nities
8、inageographicinformationsystem.Thisspatialdatab
