Title
Good properties of similarity measures and their complementarity
Author
Faculty/Department
Faculty of Social Sciences. Instructional and Educational Sciences
Publication type
article
Publication
Washington, D.C. ,
Subject
Documentation and information
Computer. Automation
Source (journal)
Journal of the American Society for Information Science and Technology. - Washington, D.C., 2001 - 2013
Volume/pages
61(2010) :10 , p. 2151-2160
ISSN
1532-2882
1532-2890
ISI
000282778400015
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Similarity measures, such as the ones of Jaccard, Dice, or Cosine, measure the similarity between two vectors. A good property for similarity measures would be that, if we add a constant vector to both vectors, then the similarity must increase. We show that Dice and Jaccard satisfy this property while Cosine and both overlap measures do not. Adding a constant vector is called, in Lorenz concentration theory, nominal increase and we show that the stronger transfer principle is not a required good property for similarity measures. Another good property is that, when we have two vectors and if we add one of these vectors to both vectors, then the similarity must increase. Now Dice, Jaccard, Cosine, and one of the overlap measures satisfy this property, while the other overlap measure does not. Also a variant of this latter property is studied.
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