On measuring association between groups of rankings in recommender systems

Abstract

A measure of association between two groups of rankings is proposed. The suggested measure possesses some interesting properties which make it useful in recommender systems and some other possible applications. In particular, it aggregates the bipolar information taking into account both the strength of the correlation and its sign. Simultaneously, applied in collaborative filtering, it rewards strong association which is a desired property in making meaningful recommendations to a user. © 2014 Springer International Publishing.