|
|
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 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. The URL for
this project is http://www.clair.si.umich.edu/iopener.
Funding
This work has been partially supported by
the National Science Foundation grant "iOPENER: A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains", jointly awarded to UMd and
UMich as
IIS
0705832.
|
People
|
| Senior Personnel |
Bonnie Dorr (Professor, University of Maryland)
Dragomir Radev (Associate Professor, University of Michigan)
Judith Klavans (Research Professor, University of Maryland )
Jimmy Lin (Assistant Professor, University of Maryland)
Ben Shneiderman (Professor, University of Maryland)
|
| Graduate Students |
Melissa Egan (Ph.D. Student, University of Maryland)
Vahed Qazvinian (Ph.D. Student, University of Michigan)
Pradeep Muthukrishnan (Ph.D. Student, University of Michigan)
Cody Dunne (Ph.D. Student, University of Maryland)
Robert Gove (Ph.D. Student, University of Maryland)
|
| Postdoctoral Researchers |
Saif Mohammad (Postdoctoral Researcher, University of Maryland)
|
| Other Affiliates |
Georg Apitz (Student Affiliate, University of Maryland)
Alex Aris (Student Affiliate, University of Maryland)
Ahmed Hassan (Student Affiliate, University of Michigan)
Chen Huang (Student Affiliate, University of Michigan)
David Zajic (Research Affiliate, University of Maryland)
|
|