Research Problems & Topics (Literature Domain). (CS598-CXZ Advanced Topics in IR Presentation) Feb 1, 2005 ChengXiang Zhai Department of Computer Science University of Illinois, Urbana-Champaign. Research Area Mining.
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(CS598-CXZ Advanced Topics in IR Presentation)
Feb 1, 2005
Department of Computer Science
University of Illinois, Urbana-Champaign
Name: Starting Point for Research in Any Area
User: Any faculty, or student who is looking at entering a new are of research.
Data Involved: All the papers/or indexed summaries available on the web.
Function: Whenever a researcher wants to enter a new area, he/she faces a big question:
How or from where should I start? Finding an answer for this question can be a difficult
or at least time consuming task. It would be great if a system exists that can gather, and
summarize all the information about all the papers (including classic, highly referenced,
cutting edge, etc) and also all the people that work in the related areas (including
summaries and information about their publications, projects, affiliations, etc). This
intelligent system can somehow generate a route through which the user can get all the
information he/she would need in order to start getting into the desired area.
In literatures, facts as cause-effect relationship are popular, especially in medical, law,
and history literature. To be able to do that, a person need to read all the related
documents, remember most of facts, and do a good reasoning. However, with a huge
number of literatures in each field today, no one could be able to do that thoroughly.
Most of attempts success with some forms of lucky which is reaching right documents at
Making this task done automatically, much useful and maybe surprised knowledge will
not be missed. And base on this, we could build some a new kind of expert system which
works directly with knowledge in form of literatures.
Users: Researchers, lawyers, historians.
Data: Existing literatures, especially literatures of medical, law, history, and chemistry.
Challenges: Recognizing and connecting causes and effects together is extremely hard.