In particular, for the pairwise and the coverage model, we show how to learn the similarity function σ(i, j) and the word importance weights ω(v) respectively.
we parameterize σ(i, j) and ω(v) using a linear model, allowing that each depends on the full set of input sentences x: In the above equations, w is a weight vector that is learned, and φ p x (i, j) and φ c x (v) are feature vectors.