Selection of Passages for Information Reduction

Proceedings of the AAAI Conference on Artificial Intelligence, 13

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 13

SIGART/AAAI Doctoral Consortium Abstracts

There currently exists a bottleneck in extracting information from pre-existing texts to generate a symbolic representation of the text that can be used by a case-based reasoning (CBR) system. Symbolic case representations are used in legal and medical domains among others. Finding similar cases in the legal domain is crucial because of the importance precedents play when arguing a case. Further, by examining the features and decisions of previous cases, an advocate or judge can decide how to handle a current problem. In the medical domain, remembering or finding cases similar to the current patient’s may be key to making a correct diagnosis: they may provide insight as to how an illness should be treated or which treatments may prove to be the most effective.