IF 0.8 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Information System Modeling and Design Pub Date : 2019-04-01 DOI:10.4018/ijismd.2019040101
Samir Sellami, T. Dkaki, N. Zarour, Pierre-Jean Charrel
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引用次数: 3

摘要

网络向数据网络和社交媒体的多样化意味着公司需要收集所有必要的数据,以帮助做出最明智的市场决策。然而,网络上的数据提供者以各种数据模型发布数据,并可能为其配备不同的搜索功能,因此需要数据集成技术来访问它们。本文探讨了该领域的当前挑战,讨论了一些现有集成工具的局限性,并通过提出一种基于语义中介的方法来解决这些问题,从而将企业数据与大规模社交和关联数据虚拟地集成在一起。所建议的方法的实现是一个可配置的中间件应用程序和一个用户友好的关键字搜索界面,该界面结合各种SPARQL端点和Web api从内部企业数据中检索其输入。进行了一项评价研究,以比较其特点与最近的整合方法。结果说明了所贡献方法的附加价值和可用性。
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MidSemI
The web diversification into the Web of Data and social media means that companies need to gather all the necessary data to help make the best-informed market decisions. However, data providers on the web publish data in various data models and may equip it with different search capabilities, thus requiring data integration techniques to access them. This work explores the current challenges in this area, discusses the limitations of some existing integration tools, and addresses them by proposing a semantic mediator-based approach to virtually integrate enterprise data with large-scale social and linked data. The implementation of the proposed approach is a configurable middleware application and a user-friendly keyword search interface that retrieves its input from internal enterprise data combined with various SPARQL endpoints and Web APIs. An evaluation study was conducted to compare its features with recent integration approaches. The results illustrate the added value and usability of the contributed approach.
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来源期刊
CiteScore
3.20
自引率
0.00%
发文量
31
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