不同质的数据集成:挑战和机遇
I Made Putrama1,2, Péter Martinek1
1Department of Electronics Technology, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary.
Data in brief
|September 17, 2024
概括
虚拟数据集成为处理动态市场需求提供了与实体系统相比具有成本效益的替代方案. 研究强调了大数据,语义挑战以及解决非结构化数据集成的必要性.
科学领域:
- 计算机科学 计算机科学
- 数据管理数据管理
- 信息系统信息系统信息系统
背景情况:
- 组织需要强大的数据集成来适应动态市场.
- 物理数据集成系统的实施和维护成本昂贵.
- 在大数据时代,虚拟数据集成成为一个具有成本效益的,研究密集的替代方案.
研究的目的:
- 提供对异质数据整合研究的全面概述.
- 专注于整合各种数据源的方法和方法.
- 确定数据集成的关键趋势,挑战和未来的研究方向.
主要方法:
- 对有关异质数据整合的现有出版物的系统调查.
- 分析各种领域的研究趋势,重点关注大数据.
- 识别普遍存在的挑战,特别是语义整合和非结构化数据.
主要成果:
- 研究是广泛的,但往往是域异的,优先考虑大数据而不是特定的应用.
- 语义挑战是数据集成研究人员的主要关注点.
- 在解决与语义和非结构化数据格式相关的整合问题方面存在重大差距.
结论:
- 需要进一步研究整合语义和非结构化数据.
- 机器学习,数据集成和隐私的交集提供了一个有前途的研究途径.
- 案例研究可以为更广泛的数据整合挑战提供有价值的见解.
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