全局模式作为本地数据集成商,使用主动学习来识别候选属性

Clóvis Santos, Carina Dorneles
{"title":"全局模式作为本地数据集成商,使用主动学习来识别候选属性","authors":"Clóvis Santos, Carina Dorneles","doi":"10.1504/ijams.2023.134427","DOIUrl":null,"url":null,"abstract":"Data integration represents a challenge in application development. Although there are several alternatives to data integration, such as federated and distributed databases, there are still problems with the standardisation of distinct data sources, and this happens because different companies develop distinct systems with different paradigms and concepts. In this paper, we present a case study, in the agriculture and environment domain, of an essential point in the data integration domain which is to show resources to identify nearby attributes concerning the characteristics of the content foreseen in the requirements presented in the proposed schema. Information technology experts in agribusiness help map the most relevant attributes for the investigated scenario. In our experimental tests, we used a quantitative method data analysis approach to validate the results with quantitative comparisons regarding the percentages of proximity between the attribute contents in the databases. Our proposal presents an alternative to simplify data integration without intermediate application or middleware layers. The results were measured on a scale between 0% and 100% to identify candidate attributes. The results were good in identifying attributes in the databases in almost 67% of the cases.","PeriodicalId":38716,"journal":{"name":"International Journal of Applied Management Science","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Global schema as local data integrator using active learning to identify candidates attributes\",\"authors\":\"Clóvis Santos, Carina Dorneles\",\"doi\":\"10.1504/ijams.2023.134427\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data integration represents a challenge in application development. Although there are several alternatives to data integration, such as federated and distributed databases, there are still problems with the standardisation of distinct data sources, and this happens because different companies develop distinct systems with different paradigms and concepts. In this paper, we present a case study, in the agriculture and environment domain, of an essential point in the data integration domain which is to show resources to identify nearby attributes concerning the characteristics of the content foreseen in the requirements presented in the proposed schema. Information technology experts in agribusiness help map the most relevant attributes for the investigated scenario. In our experimental tests, we used a quantitative method data analysis approach to validate the results with quantitative comparisons regarding the percentages of proximity between the attribute contents in the databases. Our proposal presents an alternative to simplify data integration without intermediate application or middleware layers. The results were measured on a scale between 0% and 100% to identify candidate attributes. The results were good in identifying attributes in the databases in almost 67% of the cases.\",\"PeriodicalId\":38716,\"journal\":{\"name\":\"International Journal of Applied Management Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Applied Management Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijams.2023.134427\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Management Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijams.2023.134427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0

摘要

数据集成是应用程序开发中的一个挑战。尽管有几种数据集成的替代方案,比如联邦数据库和分布式数据库,但是不同数据源的标准化仍然存在问题,这是因为不同的公司使用不同的范例和概念开发不同的系统。在本文中,我们提出了一个农业和环境领域的案例研究,该案例研究了数据集成领域中的一个关键点,即显示资源以识别与所提出模式中所提出的需求中所预见的内容的特征相关的附近属性。农业综合企业的信息技术专家帮助为所调查的场景绘制最相关的属性。在我们的实验测试中,我们使用定量方法数据分析方法,通过对数据库中属性内容之间的接近百分比进行定量比较来验证结果。我们的建议提供了一种替代方案,可以在没有中间应用程序或中间件层的情况下简化数据集成。结果在0%到100%之间进行测量,以确定候选属性。在几乎67%的情况下,结果很好地识别了数据库中的属性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Global schema as local data integrator using active learning to identify candidates attributes
Data integration represents a challenge in application development. Although there are several alternatives to data integration, such as federated and distributed databases, there are still problems with the standardisation of distinct data sources, and this happens because different companies develop distinct systems with different paradigms and concepts. In this paper, we present a case study, in the agriculture and environment domain, of an essential point in the data integration domain which is to show resources to identify nearby attributes concerning the characteristics of the content foreseen in the requirements presented in the proposed schema. Information technology experts in agribusiness help map the most relevant attributes for the investigated scenario. In our experimental tests, we used a quantitative method data analysis approach to validate the results with quantitative comparisons regarding the percentages of proximity between the attribute contents in the databases. Our proposal presents an alternative to simplify data integration without intermediate application or middleware layers. The results were measured on a scale between 0% and 100% to identify candidate attributes. The results were good in identifying attributes in the databases in almost 67% of the cases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Applied Management Science
International Journal of Applied Management Science Business, Management and Accounting-Strategy and Management
CiteScore
1.20
自引率
0.00%
发文量
21
期刊最新文献
Investigating the determinants of mobile shopping applications continuance usage intention in the post covid-19 pandemic A comparative study of static and iterative models of ARIMA and SVR to predict stock indices prices in developed and emerging economies A comparative study of static and iterative models of ARIMA and SVR to predict stock indices prices in developed and emerging economies An optimal Bayesian acceptance sampling plan using decision tree method The multi-criteria group decision-making FlowSort method using the output aggregation
×
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