{"title":"NORMS: An automatic tool to perform schema label normalization","authors":"S. Sorrentino, S. Bergamaschi, M. Gawinecki","doi":"10.1109/ICDE.2011.5767952","DOIUrl":null,"url":null,"abstract":"Schema matching is the problem of finding relationships among concepts across heterogeneous data sources (heterogeneous in format and structure). Schema matching systems usually exploit lexical and semantic information provided by lexical databases/thesauri to discover intra/inter semantic relationships among schema elements. However, most of them obtain poor performance on real world scenarios due to the significant presence of “non-dictionary words”. Non-dictionary words include compound nouns, abbreviations and acronyms. In this paper, we present NORMS (NORMalizer of Schemata), a tool performing schema label normalization to increase the number of comparable labels extracted from schemata1.","PeriodicalId":332374,"journal":{"name":"2011 IEEE 27th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 27th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2011.5767952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Schema matching is the problem of finding relationships among concepts across heterogeneous data sources (heterogeneous in format and structure). Schema matching systems usually exploit lexical and semantic information provided by lexical databases/thesauri to discover intra/inter semantic relationships among schema elements. However, most of them obtain poor performance on real world scenarios due to the significant presence of “non-dictionary words”. Non-dictionary words include compound nouns, abbreviations and acronyms. In this paper, we present NORMS (NORMalizer of Schemata), a tool performing schema label normalization to increase the number of comparable labels extracted from schemata1.
模式匹配是跨异构数据源(格式和结构都是异构的)查找概念之间关系的问题。模式匹配系统通常利用词汇数据库/词典提供的词汇和语义信息来发现模式元素之间的语义内/语义间关系。然而,由于“非字典单词”的大量存在,它们中的大多数在现实场景中表现不佳。非词典词汇包括复合名词、缩略语和首字母缩略词。在本文中,我们提出了norm (NORMalizer of Schemata),一个执行模式标签规范化的工具,以增加从schemata1中提取的可比较标签的数量。