ITR: Shallow Integration over the Deep Web: A Holistic Approach

ITR：深网浅层集成：整体方法

• 批准号: 0313260
• 负责人: Kevin Chang
• 金额: $ 30万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0313260&HistoricalAwards=false
• 关键词: ITR; Shallow; Integration; over; Deep

This project aims to build a MetaIntegrator for integrating databases on the Internet. To realize large-scale integration over this "deep Web," the research pursues the "shallow integration" philosophy, which does not rely on deep semantic annotations or deep probing of sources. In particular, it takes a holistic approach, which essentially leverages the challenge of large-scale itself as an opportunity, by resorting to hidden statistical regularities for enabling shallow integration. Specifically, this project focuses on three tasks: (1) Deep Web survey: To characterize the nature of the deep Web (as pertinent to semantic integration), this project extensively surveys databases on the Web. (2) Source selection: Since there are so many potential sources, "what sources should be involved in answering a given query?" This project thus develops the dynamic selection of sources for matching a query. (3) Schema integration: Since sources are heterogeneous, in querying the problem "how does an attribute in one source correspond to that in another?" Needs to be resolved. This project thus studies the matching and unification of schemas across myriad sources. Information on this project will be posted on the Web (http://eagle.cs.uiuc.edu/metaquerier) and the results are expected to have broad impact by advancing the understanding of dynamic, large-scale integration and develop a set of general techniques, and constructing a MetaIntegrator for providing access to (selected domains of) the deep Web. These fundamental results are likely to have technology transfer into a broad spectrum of Web applications.

本项目旨在构建一个MetaIntegrator，用于集成Internet上的数据库。为了实现大规模的集成在这个“深网”，研究追求的“浅集成”的哲学，它不依赖于深语义注释或深探测的来源。特别是，它采取了一种整体的方法，基本上是利用大规模本身的挑战作为一个机会，通过诉诸隐藏的统计数据来实现浅层整合。具体来说，该项目主要关注三个任务：（1）Deep Web调查：为了描述deep Web的性质（与语义集成相关），该项目广泛调查了Web上的数据库。(2)来源选择：既然有这么多潜在的来源，“在回答给定的查询时应该涉及哪些来源？“因此，该项目开发了用于匹配查询的源的动态选择。(3)模式集成：由于源是异构的，在查询“一个源中的属性如何对应于另一个源中的属性？“需要解决。因此，这个项目研究了跨越无数来源的模式的匹配和统一。有关这一项目的信息将张贴在网上（http：//eagle.cs.uiuc.edu/metaquerier），预计其结果将产生广泛的影响，促进对动态、大规模集成的理解，开发一套通用技术，并构建一个MetaIntegrator，提供对深层网（选定领域）的访问。这些基本的结果很可能将技术转移到广泛的Web应用程序中。