I have two word embeddings $w_1$ and $w_2$ with dimension 100 as input to a convolutional neural network. It should learn the similarity between these two words.
I am now concerned with the applied convolution operation. What is a reasonable filter size? In which way should the convolution operation perform on the two word embeddings?