Large Scale Matching Issues and Advances

S. Sellami, A. Benharkat, Y. Amghar
{"title":"Large Scale Matching Issues and Advances","authors":"S. Sellami, A. Benharkat, Y. Amghar","doi":"10.4018/978-1-61520-859-3.CH009","DOIUrl":null,"url":null,"abstract":"Nowadays, the Information technology domains (semantic web, E-business, digital libraries, life science, etc) abound with a large variety of data (e.g. DB schemas, XML schemas, ontologies) and bring up a hard problem: the semantic heterogeneity. Matching techniques are called to overcome this challenge and attempts to align these data. In this chapter, the authors are interested in studying large scale matching approaches. They survey the techniques of large scale matching, when a large number of schemas/ontologies and attributes are involved. They attempt to cover a variety of techniques for schema matching called Pair-wise and Holistic, as well as a set of useful optimization techniques. They compare the different existing schema/ontology matching tools. One can acknowledge that this domain is on top of effervescence and large scale matching needs many more advances. Then the authors provide conclusions concerning important open issues and potential synergies of the technologies presented.","PeriodicalId":169003,"journal":{"name":"Ontology Theory, Management and Design","volume":"240 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ontology Theory, Management and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-61520-859-3.CH009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Nowadays, the Information technology domains (semantic web, E-business, digital libraries, life science, etc) abound with a large variety of data (e.g. DB schemas, XML schemas, ontologies) and bring up a hard problem: the semantic heterogeneity. Matching techniques are called to overcome this challenge and attempts to align these data. In this chapter, the authors are interested in studying large scale matching approaches. They survey the techniques of large scale matching, when a large number of schemas/ontologies and attributes are involved. They attempt to cover a variety of techniques for schema matching called Pair-wise and Holistic, as well as a set of useful optimization techniques. They compare the different existing schema/ontology matching tools. One can acknowledge that this domain is on top of effervescence and large scale matching needs many more advances. Then the authors provide conclusions concerning important open issues and potential synergies of the technologies presented.
大规模匹配问题和进展
如今,信息技术领域(语义网、电子商务、数字图书馆、生命科学等)充斥着各种各样的数据(如DB模式、XML模式、本体),这就带来了一个难题:语义异构。需要使用匹配技术来克服这一挑战,并尝试对齐这些数据。在本章中,作者感兴趣的是研究大规模匹配方法。他们调查了涉及大量模式/本体和属性时的大规模匹配技术。它们试图涵盖各种模式匹配技术,称为成对匹配和整体匹配,以及一组有用的优化技术。它们比较了不同的现有模式/本体匹配工具。我们可以承认,这个领域是在泡沫之上的,大规模的匹配需要更多的进步。然后,作者就重要的开放问题和所提出的技术的潜在协同作用提供结论。
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信