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ID:36564127
大小:5.03 MB
页数:153页
时间:2019-05-12
《知识网格及其教育应用的关键技术研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、电子科技大学博士学位论文知识网格及其教育应用的关键技术研究姓名:韩永国申请学位级别:博士专业:计算机应用技术指导教师:孙世新20060301动态服务组合的构造算法和最优组合算法,保证了组合服务的健壮性,提高了服务的可用性。关键词:知识网格,本体,知识测量,个性化学习服务,智能学习系统IIABSTRACTThefocusofthedissertationiskeytechnologiesofbuildingknowledgegridandofassistinglearningbyknowledgegrid.Knowl
2、edgemeasurement,knowledgerepresentation,andontologyarestudied.Thechangesinlearningviewpointandevolvementoflearningsystemarecommentedon.Thecharacteristicsoflearningprocessandinformationprocessarecompared.Athoroughanalysisofemeringtechnologies,theirachivements,o
3、bstaclestoovercome,andongoingconvergenceamongthem,ismade.Emergingtechnologiesconcernedwithourpurposearegrid,semanticweb,serviceorientedarchitecture,semanticgrid,andmulti-agentsystem.Withthepurposeinmindofintegratingknowledgeproperties,learningprinciplesandemer
4、ingtechnologies,asmartlearningsystemisproposed.Thereaserchissupportedbythehi-techresearchanddevelopmentprogramofchinaundergrantNo.2003AAll6060.Following眦contributionsofthedissertation:1.Aformulaofcomputingknowledgeperformanceisproposed.Basedonthediscussionabou
5、tinformationprocessandlearningprocess,alearningmodelisbuilt.Theperformanceofknowledgeinthelearningmodelismeasuredbytheamountsofproblemresolvedbytheknowledge.Theformulaproposedprovidesasupplementtoknowledgemeasurementandisofimportancetoknowledgemanagement,knowl
6、edgediscovery,knowledgeperformanceevaluationandknowledgelearning.2.Asmartlearningspace(SLS)basedonsemanticgridtechnologyisproposed,andtheDescriptiveLogicmodelofSLSisgiven.WiththepurposeofassistingthelearningactivityonInteract,theSLSiscomposedofknowledgespace,c
7、onditionspaceandparticipantspace.TheprominentfeaturesofSLSCanbeclaimedas(1)explicitlocationoflearningprinciple,(2)technologyfromsemanticgrid,(3)foundationonDescriptiveLogic,and(4)personizedlearningsupport.3.Amethodofprovidingpersonizedlearningisproposed.Learne
8、rprofilespaceisconstructedandisusedasrulesofselectingpersonizedlearningcontent.Threetypicalservicesofnarrative,analogyandargumentlearningareproposedanddesignedbythemethodofgridcomp
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