利用深层网络：现在和未来
Harnessing the Deep Web: Present and Future
摘要：
在过去的几年里，我们建立了一个系统，向Google.com用户展示了大量的Deep-Web内容。我们的系统显示的内容每秒可提供超过1000个搜索查询，涵盖50多种语言和数百个领域。Deep Web长期以来一直被认为是Web上结构化数据的主要来源，因此访问Deep Web内容长期以来一直是数据管理社区感兴趣的问题。在本文中，我们报告了我们认为深网提供价值的地方，以及它没有提供价值的地方。我们对比了两种非常不同的方法来公开Deep-Web内容--我们使用的表面方法和数据管理文献中经常采用的虚拟集成方法。我们强调这两种方法的价值所在，并警告潜在的陷阱。我们概述了未来研究的重要领域，特别是强调了可以从分析网络上大量可能不同的结构化数据中获得的价值。
英文摘要：
Over the past few years, we have built a system that has exposed large volumes of Deep-Web content to Google.com users. The content that our system exposes contributes to more than 1000 search queries per-second and spans over 50 languages and hundreds of domains. The Deep Web has long been acknowledged to be a major source of structured data on the web, and hence accessing Deep-Web content has long been a problem of interest in the data management community. In this paper, we report on where we believe the Deep Web provides value and where it does not. We contrast two very different approaches to exposing Deep-Web content -- the surfacing approach that we used, and the virtual integration approach that has often been pursued in the data management literature. We emphasize where the values of each of the two approaches lie and caution against potential pitfalls. We outline important areas of future research and, in particular, emphasize the value that can be derived from analyzing large collections of potentially disparate structured data on the web.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
