ITR: Data on the Deep Web: Queries, Trawls, Policies and Countermeasures

ITR：深网数据：查询、拖网、政策和对策

• 批准号: 0205647
• 负责人: Joseph Hellerstein
• 金额: $ 167.5万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-10-01 至 2007-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205647&HistoricalAwards=false
• 关键词: ITR; Data; Deep; Web; Queries

The volume of hypertext on the World Wide Web is dwarfed by the amountof data made available in networked databases, which has been estimated to be 400 to 550 times larger than the WWW hypertext. This proposal refers to this data as the Federated Facts and Figures on the Internet, or simply the FFF. The goal of this work is to explore the mechanisms for -- and consequences of -- aggressively leveraging this resource.The proposal has three aspects. First, it describes algorithms and systems for exploiting facts and figures on the Internet. In particular, it proposes adaptive query processing for the Telegraph system, to adjust to the volatility characteristic of the Internet. It also proposes extending Telegraph to ``trawl'' large amounts of data from the FFF, by running recursive queries over multiple data sources. The second goal of the proposal is to explore the ramifications of providing FFF tools to the broad Internet user base. This includes an investigation of policy -- both social and technical -- and the economic incentives and ramifications surrounding such policies. The third goal is to explore the design space of countermeasures that can prevent FFF technologies from being misused..

万维网上的超文本的数量与网络数据库中提供的数据量相比相形见绌，据估计，这些数据量是万维网超文本的400到550倍。该提案将这些数据称为互联网上的联合事实和数字，或简称FFF。这项工作的目标是探索积极利用这一资源的机制及其后果。首先，它描述了利用互联网上的事实和数字的算法和系统。特别提出了对电报系统进行自适应的查询处理，以适应互联网的波动性特征。它还建议通过在多个数据源上运行递归查询，将Telegraph扩展到来自FFF的大量数据。该提案的第二个目标是探讨向广大互联网用户提供FFF工具的后果。这包括对政策的调查--包括社会政策和技术政策--以及围绕这些政策的经济激励和后果。第三个目标是探索可以防止FFF技术被滥用的对策的设计空间。