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. © 2011 Springer-Verlag.
CITATION STYLE
Rissland, E. L., & Xu, X. (2011). Using case-based tests to detect gray cygnets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6880 LNAI, pp. 258–273). https://doi.org/10.1007/978-3-642-23291-6_20
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