Rough Set Based Ontology Matching

Int. J. Rough Sets Data Anal. Pub Date : 2018-04-01 DOI:10.4018/IJRSDA.2018040103

Saruladha Krishnamurthy, A. Janardanan, B. Akoramurthy

{"title":"Rough Set Based Ontology Matching","authors":"Saruladha Krishnamurthy, A. Janardanan, B. Akoramurthy","doi":"10.4018/IJRSDA.2018040103","DOIUrl":null,"url":null,"abstract":"Ontologiesenrichestheknowledgeandaddmeaningtothedataresidinginsemanticweb.Ontology matchingidentifiesconceptsformatchinginsourceontologiestothetargetontologiestoeliminate heterogeneities.Despiteusing similaritymeasures for identifying similar concepts, theontology matchingsystemsfailstohandleuncertainty.Thispaperproposesaroughsetbasedontologymatching systemtohandleuncertaintywhichaims(i)tooptimizeconceptsconsideredformatchingbyusing concepttypeclassification(ii)touseroughsetconceptsusingindiscernibilityrelationsandreducts (iii)toapplycriterionofrealism–adecisionmakingunderuncertaintycriteria.Theexperiments conductedintheOAEIbenchmarkdatasets,RSOMsystemyieldedanincreaseof8%inprecision. Thecombinedapproachofusingreductandindiscenibiltyrelationsreducesthenumberofconcepts consideredformatchingamonguncertainentitiestoabout70%incomparisontotheexistingsystems andincreasestheaccuracyofresultsbyusingcriterionofrealism. KeywORDS Criterion of Realism, Ontology Matching, Reduct, Rough Sets, Uncertainty","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Rough Sets Data Anal.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJRSDA.2018040103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 10

Abstract

Ontologiesenrichestheknowledgeandaddmeaningtothedataresidinginsemanticweb.Ontology matchingidentifiesconceptsformatchinginsourceontologiestothetargetontologiestoeliminate heterogeneities.Despiteusing similaritymeasures for identifying similar concepts, theontology matchingsystemsfailstohandleuncertainty.Thispaperproposesaroughsetbasedontologymatching systemtohandleuncertaintywhichaims(i)tooptimizeconceptsconsideredformatchingbyusing concepttypeclassification(ii)touseroughsetconceptsusingindiscernibilityrelationsandreducts (iii)toapplycriterionofrealism–adecisionmakingunderuncertaintycriteria.Theexperiments conductedintheOAEIbenchmarkdatasets,RSOMsystemyieldedanincreaseof8%inprecision. Thecombinedapproachofusingreductandindiscenibiltyrelationsreducesthenumberofconcepts consideredformatchingamonguncertainentitiestoabout70%incomparisontotheexistingsystems andincreasestheaccuracyofresultsbyusingcriterionofrealism. KeywORDS Criterion of Realism, Ontology Matching, Reduct, Rough Sets, Uncertainty

查看原文本刊更多论文

基于粗糙集的本体匹配

Ontologiesenrichestheknowledgeandaddmeaningtothedataresidinginsemanticweb。Ontology matchingidentifiesconceptsformatchinginsourceontologiestothetargetontologiestoeliminate异质性。Despiteusing similaritymeasures用于识别类似的概念，theontology matchingsystemsfailstohandleuncertainty。Thispaperproposesaroughsetbasedontologymatching systemtohandleuncertaintywhichaims(i)tooptimizeconceptsconsideredformatchingbyusing concepttypeclassification(ii)touseroughsetconceptsusingindiscernibilityrelationsandreducts (iii)toapplycriterionofrealism -adecisionmakingunderuncertaintycriteria。Theexperiments conductedintheOAEIbenchmarkdatasets，RSOMsystemyieldedanincreaseof8%inprecision。Thecombinedapproachofusingreductandindiscenibiltyrelationsreducesthenumberofconcepts consideredformatchingamonguncertainentitiestoabout70%incomparisontotheexistingsystems andincreasestheaccuracyofresultsbyusingcriterionofrealism。关键词:真实感标准，本体匹配，约简，粗糙集，不确定性

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Int. J. Rough Sets Data Anal.

自引率

0.00%

发文量