EAGER: T2K: From Tables to Knowledge

网络让人类变得更聪明，提供了获取大量知识和事实的便捷途径。语义网也有能力通过让计算机程序和设备访问海量的数据、事实和知识来增强它们的能力。该项目正在探索直接从电子表格、数据库关系和文档表中的数据中自动提取新知识的可行性，并将其表示为语义Web语言RDF中高度可互操作的链接开放数据（LOD）。抽取由概率图形模型指导，该模型使用从当前LOD知识资源中挖掘的统计信息。为了证明这项研究的潜在回报，该系统被用于从医学期刊和data.gov等网站上收集的表格中提取知识。虽然使用W3C语义网络语言RDF和OWL来表示知识，但结果也适用于其他语义数据框架，如Microdata （Search Consortium）、Freebase （b谷歌）、Probase （Microsoft）和Open Graph （Facebook）。开源的原型软件允许其他研究人员进行实验，从他们的领域的表中自动生成语义丰富的数据。如果成功，这样的软件提取系统有望成为新的在线知识生态的一部分——既消费现有的LOD知识来理解表中隐含的预期含义，又产生新的事实和知识，这些事实和知识将成为Web的一部分。这代表了公共语义数据的广度和深度的急剧增加，可以使“大数据”分析更有效。

The Web has made humans smarter, providing ready access to vast amounts of knowledge and facts. The Semantic Web has the capacity to similarly enhance computer programs and devices by giving them access to enormous volumes of data, facts and knowledge. This project is exploring the feasibility of automatically extracting new knowledge directly from data found in spreadsheets, database relations, and document tables and representing it as highly interoperable linked open data (LOD) in the Semantic Web language RDF. The extraction is guided by probabilistic graphical models that use statistical information mined from current LOD knowledge resources. To demonstrate the potential payoff of the research, the system is used to extract knowledge from tables collected from medical journals and tables from web sites like data.gov. While the W3C semantic web languages RDF and OWL are used to represent the knowledge, the results are applicable to other semantic data frameworks such as Microdata (Search Consortium), Freebase (Google), Probase (Microsoft) and the Open Graph (Facebook). The open sourced prototype software allows other researchers to experiment with automatically producing semantically enriched data from tables for their domains.If successful, such software extraction systems are expected to become part of a new online knowledge ecology -- both consuming existing LOD knowledge to understand the intended meaning implicit in a table and producing new facts and knowledge that will become part of Web. This represents a dramatic increase in the breadth and depth of public semantic data that can make "big data" analytics more effective.