Digital Government: A Language-Modeling Approach To Metadata for Cross-Database Linkage and Search

数字政府：跨数据库链接和搜索元数据的语言建模方法政府在线服务的一个关键问题是，相关信息通常保存在不同机构的不同系统中，因此很难整合这些信息。由于这个原因，大多数政府“一站式购物”网站的尝试都失败了；它们必须手动维护，随着时间的推移，这是行不通的。另一方面，由于政府持有的信息的分布式性质，数据仓库（数据被清理、统一并存放在一个中央位置）将不起作用。解决这个问题的一个有希望的途径是通过使用自动化系统，为各种数据集生成元数据（关于数据的数据），使它们更容易集成，而原始数据仍保留在其主站点。本提案的工作将以一种新的方式——语言建模来解决这个问题。政府合作者是美国地质调查局、美国商务部、总务管理局和美国国会图书馆。

EIA9983253Callan JamieCarnegie Mellon UniversityDigital Government: A Language Modeling Approach to Metadata for Cross-Database Linkage and SearchA crucial problem in government on-line services is that related information is often maintained in different systems across different agencies, thus making it difficult to integrate that information. Most attempts at "one-stop shopping" sites in the government fail for that reason; they must be maintained manually which does not work over time. On the other hand, data warehousing, where the data is cleaned, made conformant and housed in a central location, will not work due to the distributed nature of government-held information.One promising avenue to approach this problem would be through the use of automated systems which generate metadata (data about data) for various datasets, allowing them to be integrated more easily, while the original data remains in place at its home site. The work of this proposal will address this problem in a new way - language modeling. The government collaborators are the US Geological Survey, the US Department of Commerce, the General Services Administration and the US Library of Congress.