基于知识本体的网络消费行为理论与方法研究

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1、基于知识的网络消费个性化服务系统推理机制与推荐结果的产生等内容，剖析了基于知识的网络消费个性化服务策略的自适应选择问题。关键词：网络消费；智能推荐；知识挖掘；语义本体分类号：F208经济信息管理；TP393．09计算机网络应用程序j匕塞交垣厶堂熊±堂僮论塞△旦S!B△￡!ABSTRACTABSTRACT：Currentrecommendersystemscannotmeetthedemandoflarge—scaleonlinemarketinginthedistributedenvironment．Thesemanticonto

2、logytechnologiesandelectronicrecommendationtechnologiestogethercanbeexploitedtorealizetheeffectiveacquisitionandfusionoftheknowledgeofproducts，userrequirementsandrecommendationfunction，andcanfurtherrealizethesynergizedcollaborationofconstituentsoftherecommendersystems

3、．Thisdissertationresearchesonthebasictheoryandmethodologyofintelligentelectroniccommercerecommendationbasedontheonlineconsumingbehaviorknowledgewhichwehopetoprovidethefundamentalsupportintheoryandmethodologyfordevelopinghighlyresponsiveandeffectiverecommendersystemsfo

4、rlarge—scaleelectronicconlmerceindistributedenvironments．Thispaperintroduceknowledgemanagementandontologyintothestudyingofonlineconsumingbehavior,andconstructedanowframework——KnowledgeOntologybasedOnlineConsumingBehavior(KOB—OCB)．Theresearchonthetheoryandmethodologyba

5、sedontheonlineconsumingbehaviorknowledgeissubdividedintofourlevelswhicharecorrelatedwitheachotherclosely．ThefirstistheonlineconsumingbehaviorknowledgeminingbasedonWEB．Thesecondistherepresentationofknowledgeforonlineconsumingbehaviorknowledge．TheⅡ1irdisthetheoryandmeth

6、odofconstructionforonlineconsumingbehavior．Andthelastistheintellectualrecommenderofonlineconsumingservicebasedonself-demand．Thisdissertationstudiedtheminingarithmeticoftheonlineconsumingbehaviorknowledge，designedtheoryandmethodologyofontologyconstructionoftheonlinecon

7、sumingbehaviorknowledge，researchedintellectualrecommendersystemsbasedonself-demandofonlineconsumingservicebased．Themaincontentofthedissertationasfollows：Therelativetheorieswereintroducedwhichincludethebasictheoryoftheonlineconsuming，constructedthedifferentbetweenonlin

8、econsumingandtraditionalconsuming，analysisedtheaffectedfactorsofonlineconsumingbehavior,discussedthepatternsofonlineconsumin