III-COR: iOPENER - A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains
III-COR: iOPENER - A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains
批准号:
0705832
负责人:
Ben Shneiderman
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-08-15 至 2011-07-31
中文摘要
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英文摘要
In today's rapidly expanding disciplines, scientists and scholars are constantly faced with the daunting task of keeping up with knowledge in their field. In addition, the increasingly interconnected nature of real-world tasks often requires experts in one discipline to rapidly learn about other areas in a short amount of time. Cross-disciplinary research requires scientists in such areas as linguistics, biology, and sociology to learn about computational approaches and applications. Both students and educators must have access to accurate surveys of previous work, ranging from short summaries to in-depth historical notes. Government decision-makers must learn about different scientific fields to determine funding priorities.The goal of iOPENER (Information Organization for PENning Expositions on Research) is to generate readily-consumable surveys of different scientific domains and topics, targeted to different audiences and levels, e.g., expert specialists, scientists from related disciplines, educators, students, government decision makers, and citizens including minorities and underrepresented groups. Surveyed material is presented in different modalities, e.g., an enumerated list of articles, a bulleted list of key facts, a textual summary, or a visual presentation with zoom and filter capabilities. The original contributions of this research are in the creation of an infrastructure for automatically summarizing entire areas of scientific endeavor by linking three available technologies: (1) bibliometric lexical link mining; (2) summarization techniques; and (3) visualization tools for displaying both structure and content.The iOPENER software and resulting surveys will be made publicly available via the project Web site (http://tangra.si.umich.edu/clair/iopener/) and research results will be presented at conferences such as the ACL, SIGIR, and ASIST, as well as to broader audiences, e.g., expert specialists, students, educators, and government decision makers. Application areas include digital government, emergency response, and public health issues.
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