Document Type
Article
Publication Date
1-21-2013
Abstract
The paper suggests a similarity function for applications of empirical similarity theory in which the notion of similarity is asymmetric. I propose defining similarity in terms of a quasimetric. I suggest a particular quasimetric and explore the properties of the empirical similarity model given this function. The proposed function belongs to the class of quasimetrics induced by skewed norms. Finally, I provide a skewness axiom that, when imposed in lieu of the symmetry axiom in the main result of Billot et al. (2008), characterizes an exponential similarity function based on a skewed norm.
Scholarly Commons Citation
Teitelbaum, Joshua C., "Asymmetric Empirical Similarity" (2013). Georgetown Law Faculty Publications and Other Works. Paper 1161.
http://scholarship.law.georgetown.edu/facpub/1161
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