Regression Framework for Learning Ranking Functions using Relative Preferences
A method and apparatus for determining a ranking function by regression using relative preference data. A number of iterations are performed in which to following is performed. The current ranking function is used to compare pairs of elements. The comparisons are checked against actual preference data to determine for which pairs the ranking function mis-predicted (contradicting pairs). A regression function is fitted to a set of training data that is based on contradicting pairs and a target value for each element. The target value for each element may be based on the value that the ranking function predicted for the other element in the pair. The ranking function for the next iteration is determined based, at least in part, on the regression function. The final ranking function is established based on the regression functions. For example, the final ranking function may be based on a linear combination of regression functions.
& Sun, G.
(2008). Regression Framework for Learning Ranking Functions using Relative Preferences. .