{"title":"Towards a Composite XML Schema Matching Approach Using Reference Ontology","authors":"Hongjie Fan, Junfei Liu, Kejun Deng","doi":"10.1109/ICISCE.2016.160","DOIUrl":null,"url":null,"abstract":"Schema matching, aiming at finding the semantic correspondence of concepts between different data sources, has become a hot research area in data integration, data exchange and other areas. Over the past few years, numerous effective schema matching methods have been proposed. In the latest years, researchers have proposed a number of matching methods, which make it possible to identify and discover the semantic correspondence between the data. But schema matching have some challenges in the form of definition, utilization, and combination of element similarity measures, especially in multiple schema matching. In this paper, we study multi-schema matching problem, and convert this issue to indirect matching problem using reference ontology. We find and locate the core word, present composite schema matching methods, and generate matching result. Our experimental results demonstrate the high performance with a well precision and recall.","PeriodicalId":6882,"journal":{"name":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","volume":"39 1","pages":"724-728"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 3rd International Conference on Information Science and Control Engineering (ICISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCE.2016.160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Schema matching, aiming at finding the semantic correspondence of concepts between different data sources, has become a hot research area in data integration, data exchange and other areas. Over the past few years, numerous effective schema matching methods have been proposed. In the latest years, researchers have proposed a number of matching methods, which make it possible to identify and discover the semantic correspondence between the data. But schema matching have some challenges in the form of definition, utilization, and combination of element similarity measures, especially in multiple schema matching. In this paper, we study multi-schema matching problem, and convert this issue to indirect matching problem using reference ontology. We find and locate the core word, present composite schema matching methods, and generate matching result. Our experimental results demonstrate the high performance with a well precision and recall.