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Investigating graphs in textual case-based reasoning
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/2052
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| Title: | Investigating graphs in textual case-based reasoning |
| Authors: | Weber, Rosina O.
Cunningham, Colleen M.
Proctor, Jason M.
Fowler, Caleb L.
Murphy, M. |
| Issue Date: | 2004 |
| Publisher: | Springer Verlag |
| Citation: | Advances in Case-Based Reasoning: Proceedings of the Seventh European Conference, ECCBR 2004: pp.573-586. |
| Abstract: | Textual case-based reasoning (TCBR) provides the ability to reason
with domain-specific knowledge when experiences exist in text. Ideally, we
would like to find an inexpensive way to automatically, efficiently, and
accurately represent textual documents as cases. One of the challenges,
however, is that current automated methods that manipulate text are not always
useful because they are either expensive (based on natural language processing)
or they do not take into account word order and negation (based on statistics)
when interpreting textual sources. Recently, Schenker et al. [1] introduced an
algorithm to convert textual documents into graphs that conserves and conveys
the order and structure of the source text in the graph representation.
Unfortunately, the resulting graphs cannot be used as cases because they do not
take domain knowledge into consideration. Thus, the goal of this study is to
investigate the potential benefit, if any, of this new algorithm to TCBR. For
this purpose, we conducted an experiment to evaluate variations of the
algorithm for TCBR. We discuss the potential contribution of this algorithm to
existing TCBR approaches. |
| URI: | http://hdl.handle.net/1860/2052 |
| Appears in Collections: | Faculty Research and Publications (IST)
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