The deep web: woven to catch the middle ground

Web-KR '13 Pub Date : 2013-11-01 DOI:10.1145/2512405.2512408
Wensheng Wu
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引用次数: 4

Abstract

The massive and diverse data sources on the Deep Web presents a serious data integration challenge. Existing virtual integration approaches suffer from slow query response, while surfacing approaches demand hefty storage space and incur huge costs in maintaining data freshness. We propose a novel hybrid integration approach that strikes a balance between the virtual and surfacing approaches. The key idea is to capture user needs in query templates and focus the integration efforts on the templates. However, realizing this approach requires innovations in template-driven query planning, query parsing, and template discovery. We elaborate on these challenges and propose our solutions.
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深网:编织来捕捉中间地带
深度网络上海量多样的数据源对数据集成提出了严峻的挑战。现有的虚拟集成方法存在查询响应缓慢的问题,而表面方法需要大量的存储空间,并且在保持数据新鲜度方面产生巨大的成本。我们提出了一种新的混合集成方法,在虚拟和表面方法之间取得平衡。关键思想是在查询模板中捕获用户需求,并将集成工作集中在模板上。然而,实现这种方法需要在模板驱动的查询规划、查询解析和模板发现方面进行创新。我们详细阐述了这些挑战并提出了解决方案。
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Leveraging related entities for knowledge base acceleration Automated faceted reporting for web analytics Windowing mechanisms for web scale stream reasoning The deep web: woven to catch the middle ground
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