基于二部图模型的大本体分块与映射-.研究

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1、ABSTRACTOntologymappingaimstobuildasemanticbridgebetweenheterogeneousontologies，throughwhichthegoalofknowledgesharingandinformationexchangingbetweendifferentontologiescanbeachievedHowever,withthecontinousdevelopmentoftheontologyapplication，thesizeofontologyisalsogrowingThen．血elarge—scale

2、ontologymappinghasbecomethehotspotsinthecurrentsemanticwebresearchThisthesiswillfocusonthelarge-scaleontologymappingresearch．Firstly,theresearchbackgroundandsignificanceofthethesisisbrieflyintroduced，then，thecurrentlarge—scaleontologypartitionandmappingmethodsaresummarizedAfter，wehaveana

3、lyzedtheproblemsofthesemethods，andpointedOutthedirectionforourworkSecondly,drawingontheideaofgraphtheory,weproposeanewmethodforlarge—scaleontologypartitionandmappingbasedonbigraphmodelComparedtotraditionalpartitionmet}10d，ourmethodusestheideaofco—partitiontopartitionthetwoontologiessynch

4、ronouslyandachiveblockmatchinginpartitionphaseItfirstcomputestheconceptualsimilaritywhichcontainstextsimilarityandlexicalsimilaritybetweenthetwoontologiesThen，aweightedbigraphisbuiltbytheconceptualsimilarityNow,thebi．partitionproblemistranslatedintoagraphpartitionproblemAfter,wefindthe1：

5、1mappinginthesubgraphsbyoptimalmatchingalgorithm，andapplytherevisedrulestoimprovethemappmgquailtyintheoptimalmatchingThirdly，againstthemappingwhichobtainedbythesimilaritylackofsemanticbackgroundknowledge，weapplytherevisedrulestorevisethecandidatemappingsetItthroughthediscoveryofthemissin

6、gmappingandeliminateconflictmappingtoobtainthefinalsemanticmappingresultsFinally,basedontheresearchabove，BigraphbasedPartitionandMapping(BGPM)systemhasbeendesignedandimplemented．Moerover,themappingeffectiveofBGPMhasbeentestedthroughusingontologysetofferedbyOAEIcomparedwiththeotherlarge—s

7、caleontologymappingsystemTheexperimentalresultsshowthatourmethodcanacquirehighpartitionqualityandgoodmappingefficiencyItalsocanfindavarietyofmappingtypesKEYWORDSlarge-scaleontology，bigraph，biparition，ontologymapping，optimalmatching，mappingrevise目录摘要IABSTRACTIII第一章绪论⋯⋯⋯⋯11