Features extracted by CNN can therefore be used instead of hand-crafted features, as they carry more useful information.
the idea behind convolution is to take the dot product of a vector of k weights w k also known as kernel vector with each k-gram in the sentence s(t) to obtain another sequence of features a max pooling operation is applied over the feature map and the maximum valueĉ(t) = max{c(t)} is taken as the feature corresponding to this particular kernel vector.