|
iDEA: Drexel E-repository and Archives >
Drexel Academic Community >
College of Information Science and Technology >
Faculty Research and Publications (IST) >
Identifying facts for TCBR
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/2041
|
| Title: | Identifying facts for TCBR |
| Authors: | Weber, Rosina O.
Waldstein, Ilya
Proctor, Jason M. |
| Issue Date: | 23-Aug-2005 |
| Citation: | Paper presented at The Sixth International Conference on Case-Based Reasoning, Chicago, IL. |
| Abstract: | This paper explores a method to algorithmically distinguish case-specific
facts from potentially reusable or adaptable elements of cases in a textual case-based
reasoning (TCBR) system. In the legal domain, documents often contain casespecific
facts mixed with case-neutral details of law, precedent, conclusions the
attorneys reach by applying their interpretation of the law to the case facts, and other
aspects of argumentation that attorneys could potentially apply to similar situations.
The automated distinction of these two categories, namely facts and other elements,
has the potential to improve quality of automated textual case acquisition. The goal
is ultimately to distinguish case problem from solution. To separate fact from other
elements, we use an information gain (IG) algorithm to identify words that serve as
efficient markers of one or the other. We demonstrate that this technique can
successfully distinguish case-specific fact paragraphs from others, and propose
future work to overcome some of the limitations of this pilot project. |
| URI: | http://hdl.handle.net/1860/2041 |
| Appears in Collections: | Faculty Research and Publications (IST)
|
Items in iDEA are protected by copyright, with all rights reserved, unless otherwise indicated.
|
www.drexel.edu
