CAREER: Intelligent Argument Generation in Text and Information Graphics

职业：文本和信息图形中的智能论证生成

• 批准号: 0132821
• 负责人: Nancy Green
• 金额: --
• 依托单位: University of North Carolina Greensboro
• 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: 2002-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0132821&HistoricalAwards=false
• 关键词: CAREER; Intelligent; Argument; Generation; Text

This is a Faculty Early Career Development (CAREER) award. The research will develop techniques for computer systems to communicate technical arguments to people without technical training, using integrated text and data graphics. It will integrate empirical methods from computational linguistics and human-computer interaction. Empirical methods will be used to determine appropriate techniques for conveying technical arguments to people with non-technical backgrounds. Initially, the project will develop analytical methods based on a corpus of human-authored multimedia presentations. For example, corpus studies can determine which features of arguments suggest where supporting graphics should be placed. Next, human-computer interaction experiments will be used to determine the effectiveness of techniques based on the analytical models, and to investigate alternatives to the techniques that are shown not to be sufficient. The resulting empirically-based techniques will be incorporated into computational models that will extend current approaches in natural language generation, automated graphic design, and intelligent multimedia presentation systems. The computational models will be demonstrated with a prototype system for genetic counseling. The educational component of this project will include new course curriculum, provide undergraduate and graduate computer science students with the opportunity to participate in research, and develop a laboratory for human-computer interaction studies that will be a resource for students and other faculty members.This CAREER award recognizes and supports the early career-development activities of a teacher-scholar who is likely to become an academic leader of the twenty-first century. Her research seeks solutions for the problem that people who lack appropriate technical training are faced with increasing responsibility for making vital decisions based on technical arguments, often involving quantitative and statistical data. If successful in the area of genetic counseling, the approach could be applied to many other areas where decision makers need help in using technical information and analyses.

这是教师早期职业发展(Career)奖。这项研究将开发计算机系统的技术，利用集成的文本和数据图形，在没有技术培训的情况下与人们交流技术论点。它将整合计算语言学和人机交互的经验方法。实验方法将被用来确定向具有非技术背景的人传达技术论点的适当技术。最初，该项目将基于人类创作的多媒体演示文稿语料库开发分析方法。例如，语料库研究可以确定论点的哪些特征建议支持图形应该放置在哪里。接下来，将使用人机交互实验来确定基于分析模型的技术的有效性，并调查被证明不够充分的技术的替代方案。由此产生的基于经验的技术将被合并到计算模型中，这些计算模型将扩展自然语言生成、自动图形设计和智能多媒体演示系统中的现有方法。这些计算模型将通过一个遗传咨询原型系统进行演示。该项目的教育部分将包括新课程课程，为本科生和研究生提供参与研究的机会，并开发一个人机交互研究实验室，作为学生和其他教职员工的资源。该职业奖表彰和支持有可能成为21世纪学术领袖的教师-学者的早期职业发展活动。她的研究旨在为这样一个问题寻找解决方案，即缺乏适当技术培训的人面临着越来越多的责任，他们需要根据技术论证做出重要决策，这些决策往往涉及定量和统计数据。如果在遗传咨询领域取得成功，这种方法可以应用于决策者在使用技术信息和分析方面需要帮助的许多其他领域。