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页数:15页
时间:2019-02-28
《extensible multi-entity models a framework for incremental model construction》由会员上传分享,免费在线阅读,更多相关内容在教育资源-天天文库。
1、ExtensibleMulti-EntityModels:AFrameworkforIncrementalModelConstructionKathrynBlackmondLaskeySuzanneM.MahoneyDepartmentofSystemsEngineeringInformationExtractionandTransport,Inc.MS5A61730N.LynnStreet,Suite502GeorgeMasonUniversityArlington,VA22209Fairfax,VA22030suzanne@iet.comklask
2、ey@gmu.eduAbstractGraphicalmodelshavebecomecommonforrepresentingprobabilisticmodelsinstatisticsandartificialintelligence.ABayesiannetworkisagraphicalmodelwhichencodesaprobabilitymodelasadirectedgraphinwhichnodescorrespondtorandomvariables,togetherwithasetofconditionaldistributio
3、nsofnodesgiventheirparents.InmostcurrentapplicationsofBayesiannetworks,afixednetworkisspecifiedtoapplytoallprobleminstances.Inferenceconsistsofconditioningoncertainrandomvariables,calledevidencevariables,andinferringthedistributionofothers,calledtargetvariables.Inmorecomplexprob
4、lemsarisinginartificialintelligence,itisusefultousethebeliefnetworkformalismtorepresentuncertainrelationshipsamongvariablesinthedomain,butitisnotpossibletouseasingle,fixedbeliefnetworktoencompassallprobleminstances.Thisisbecausethenumberofentitiestobereasonedaboutandtheirrelatio
5、nshipstoeachothervariesfromprobleminstancetoprobleminstance.Thispaperdescribesaframeworkforrepresentingprobabilisticknowledgeasfragmentsofbeliefnetworksandamethodforconstructingsituation-specificbeliefnetworksforparticularprobleminstances.1.IntroductionThewidespreaddissemination
6、ofthetechnologyofgraphicalmodelshasenabledaquantumleapinthecomplexityofproblemsthatcanbeaddressedbyBayesianmethods.Agraphicalmodelisaparsimoniousandmodularparameterizationforajointprobabilitydistributiononasetofrandomvariables.Theprobabilitydistributionisexpressedasaproductoffac
7、tors,whereeachfactorinvolvesonlyasmallnumberofvariables.Thefactorizationpermitsthedistributiontobespecifiedusingamanageablenumberofparameters.Computationallyefficientgeneralpurposemethodsexistforinferringorapproximatingconditionaldistributionsofsomevariablesinagraphicalmodelgive
8、nothervariables.Alargeliteraturehasgrownontheto
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