III: Small: RUI: Collaborative Research: Exploiting Information Graphics in a Digital Library

III：小：RUI：协作研究：在数字图书馆中利用信息图形

• 批准号: 1016900
• 负责人: Stephanie Schwartz
• 金额: $ 10.49万
• 依托单位: Millersville University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1016900&HistoricalAwards=false
• 关键词: III; Small; RUI; Collaborative; Research

This project is a collaborative effort between the University of Delaware and Millersville University. Information graphics (non-pictorial graphics such as bar charts and line graphs) occur frequently in popular media such as newspapers and magazines. Not only is the knowledge conveyed by these graphics very often not included in the article's text, but (in contrast with scientific documents) the article's text most often does not even explicitly refer to the graphics. Information retrieval research has focused on the text of documents, and their information graphics have largely been ignored. Yet, the graphic designer considered the graphic's message important enough to warrant designing a graphic to convey it. This project's goal is a novel methodology for retrieving relevant information graphics from a digital library in response to user queries.Information graphics in popular media generally have a communicative goal or message that they are intended to convey. This message encapsulates the high-level knowledge contained in the graphic. The approach of the project is a language model that treats the relevance of a graphic to a query as a mixture of three components: a graphic's intended message, other textual components of the graphic such as its caption and additional textual description augmenting the caption, and the text of the document containing the graphic. Challenges that are being addressed include identifying the portion of the article that is relevant to the graphic, associating query terms with the intended messages of graphics in the document library, expanding the abbreviated captions and additional textual descriptions of graphics to more fully capture their content, and appropriately weighting the contribution of individual components of the mixture model. In addition, some kinds of graphics, such as grouped bar charts, have both a primary intended message and a secondary message. The impact of the secondary message on retrieval when an ideal graphic is unavailable is also being addressed. Evaluation of the graph retrieval methodology consists of experiments in which human subjects rate the relevance of retrieved graphics to user queries.The goal of this project is to produce a system for retrieving relevant information graphics, thereby expanding the utility of digital libraries. Together with the SIGHT system, which conveys the content of information graphics via speech, the project will extend the information resources available to individuals with sight-impairments. The project will also produce a corpus of information graphics and their XML representations that can be used by other researchers. Corpora and research results will be disseminated on the project web site (http://www.cis.udel.edu/~carberry/Graph-Retrieval). In addition to significantly increasing the resources accessible from a digital library, the research will lay the foundation for expanding research on question-answering to take into account information graphics. The project will contribute to the development of future scientists by educating graduate students, providing research opportunities for undergraduates at a predominantly undergraduate institution, and enhancing the mentoring skills of graduate students as they work on a team that includes undergraduates.

该项目是特拉华州大学和米勒斯维尔大学之间的合作努力。 信息图形（非图像图形，如条形图和线形图）经常出现在报纸和杂志等大众媒体中。 不仅是这些图形传达的知识往往不包括在文章的文字，但（与科学文献相比）文章的文字往往甚至没有明确提到的图形。 信息检索的研究主要集中在文档的文本上，其信息图形在很大程度上被忽视。 然而，图形设计师认为图形的信息重要到足以保证设计一个图形来传达它。这个项目的目标是一个新的方法，从数字图书馆检索相关的信息图形，以响应用户的查询。在流行媒体的信息图形通常有一个沟通的目标或消息，他们打算传达。 此消息封装了图形中包含的高级知识。 该项目的方法是一种语言模型，它将图形与查询的相关性视为三个组成部分的混合物：图形的预期信息，图形的其他文本组成部分，如标题和附加的文本描述，以及包含图形的文档的文本。 正在解决的挑战包括确定的部分文章是相关的图形，关联查询条件与预期的消息的图形在文档库中，扩展的缩写标题和额外的文字描述的图形，以更充分地捕捉其内容，并适当加权的混合模型的各个组件的贡献。 此外，某些类型的图形，如分组条形图，既有主要的预期消息，也有次要消息。 当一个理想的图形不可用时，次要信息对检索的影响也正在得到解决。图形检索方法的评价包括实验中，人类受试者率检索图形的相关性，以用户querions.The项目的目标是产生一个系统，检索相关的信息图形，从而扩大数字图书馆的效用。该项目与通过语音传达信息图形内容的SIGHT系统一起，将扩大有视力障碍者可利用的信息资源。该项目还将产生一个信息图形及其XML表示的语料库，可供其他研究人员使用。语料库和研究结果将在项目网站上传播（http：//www.cis.udel.edu/Graph-Retrieval）。 除了显著增加从数字图书馆获得的资源外，这项研究还将为扩大问答研究奠定基础，以考虑到信息图形。 该项目将通过教育研究生，为本科生提供研究机会，并提高研究生在包括本科生在内的团队中工作时的指导技能，为未来科学家的发展做出贡献。