Using case-based tests to detect gray cygnets

Authors:
Edwina L. Rissland;Xiaoxi Xu
Affiliations:
Department of Computer Science, University of Massachusetts, Amherst, MA;Department of Computer Science, University of Massachusetts, Amherst, MA
Venue:
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Year:
2011

Citing 5
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Abstract

Black Swans are surprising, exceptional, provocative cases that instigate major change. Gray Cygnets follow a Black Swan, are highly similar to it, are also exceptional in outcome, and continue to provoke change. We discuss experiments with a family of tests designed to detect Gray Cygnet (GC) cases in a stream of cases following a known Black Swan case. Using the two classic CBR measures of lattice-based and nearest neighbor similarity, the tests use positional information about the Black Swan in the analysis of a new case, such as its being a supreme on-point case (sopc), a Level 1 (L1) case, or in the first ring of nearest neighbors (NN#1), to determine if it is a potential GC. The idea is that a case very similar to a known Black Swan might be a GC. Experiments performed on a corpus of cases from a well-known episode in legal history spanning the era from mid-1800's to mid-1900's showed tests using sopc's were very precise, while those using L1 cases had good recall.