CAREER: An Integrated Framework for Extracting and Utilizing Information from Tables and Figures in Digital Libraries

“该奖项是根据2009年《美国复苏和再投资法案》(公法111-5)资助的。”该项目涉及检索网络上数字文档中的表格、数字和参考文献中包含的信息。目前，文件中表格和图表中存在的大量信息不容易通过自动化方法获取。终端用户不能自信地提出查询并直接通过搜索引擎检索文档中的表格和图表中显示的数据。虽然已经有大量关于表边界检测的研究和一些关于表内容提取的研究，但这些方法都没有试图识别数据并将其从表和图中存在的元数据中分离出来，这将是向前迈出的重要一步。该方案的研究目标是为数字文档处理和信息检索做出基础性贡献。目标是清楚地识别数据，自动将其从元数据中分离出来，并存储在数字存储库中。最终用户将能够有效地查询和检索数据集或其感兴趣的部分。

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."This project is concerned with retrieval of information contained in the tables, figures and references contained in digital document on the web. At present a large amount of information present in tables and figures in documents is not easy accessible by automated methods. End-users cannot confidently pose a query and retrieve data presented in tables and figures in documents directly through a search engine. While there has been substantial research on table boundary detection and some research on table content extraction, none of these methods tried to identify the data and segregate it from the metadata present in the tables and figures which would represent a significant step forward. The research goal of this proposal is to make fundamental contributions in digital document processing and information retrieval. The objective is to identify data clearly, separate it from the metadata automatically, and store in a digital repository. An end-user will then be able to effectively query and retrieve datasets or their interesting parts.