Information Technology Reference
Learning process of
2.4.2 Ranking with Large Margin Principles
Shashua and Levin [ 20 ] try to use the SVM technology to learn the model parameter
w and thresholds b k (k
1 ,...,K) for ordinal regression.
Specifically, two strategies are investigated. The first one is referred to as the
fixed-margin strategy .
Given n training queries
1 , their associated documents x (i)
q i }
and the corresponding relevance judgments y (i)
1 , the learning process
is defined below, where the adoption of a linear scoring function is assumed. The
constraints basically require every document to be correctly classified into its target
ordered category, i.e., for documents in category k , w T x (i j should exceed threshold
b k − 1 but be smaller than threshold b k , with certain soft margins (i.e., 1
− ξ (i) ∗
− ξ (i)
2 controls the complexity of the
j,k ), respectively (see Fig. 2.4 ). The term
model w .