Semantic Schema Matching for String Attribute with Word Vectors and its Evaluation

K. Nozaki, T. Hochin, Hiroki Nomiya
{"title":"Semantic Schema Matching for String Attribute with Word Vectors and its Evaluation","authors":"K. Nozaki, T. Hochin, Hiroki Nomiya","doi":"10.2991/IJNDC.K.190710.001","DOIUrl":null,"url":null,"abstract":"Instance-based schema matching is to determine the correspondences between heterogeneous databases by comparing instances. Heterogeneous databases consist of an enormous number of tables containing various attributes, causing the data heterogeneity. In such cases, it is effective to consider semantic information. In this paper, we propose the instance-based schema matching considering attributes’ semantics. We used Word2Vec to match attributes of character strings. The result shows a possibility to detect matching between attributes with high semantic similarity.","PeriodicalId":318936,"journal":{"name":"Int. J. Networked Distributed Comput.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Networked Distributed Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/IJNDC.K.190710.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Instance-based schema matching is to determine the correspondences between heterogeneous databases by comparing instances. Heterogeneous databases consist of an enormous number of tables containing various attributes, causing the data heterogeneity. In such cases, it is effective to consider semantic information. In this paper, we propose the instance-based schema matching considering attributes’ semantics. We used Word2Vec to match attributes of character strings. The result shows a possibility to detect matching between attributes with high semantic similarity.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于词向量的字符串属性语义模式匹配及其求值
基于实例的模式匹配是通过比较实例来确定异构数据库之间的对应关系。异构数据库由大量包含各种属性的表组成,导致数据异构。在这种情况下,考虑语义信息是有效的。本文提出了一种考虑属性语义的基于实例的模式匹配方法。我们使用Word2Vec来匹配字符串的属性。结果表明,可以检测具有高语义相似度的属性之间的匹配。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Adaptive Parameter Tuning for Constructing Storage Tiers in an Autonomous Distributed Storage System Application of 2‑gram and 3‑gram to Obtain Factor Scores of Statements Posted at Q&A Sites Bountychain: Toward Decentralizing a Bug Bounty Program with Blockchain and IPFS Secure Communications by Tit-for-Tat Strategy in Vehicular Networks Vehicle Platooning Systems: Review, Classification and Validation Strategies
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1