wordnet,cosine-similarity,word2vec,sentence-similarity

What I ended up doing, was taking the mean of each set of vectors, and then applying cosine-similarity to the two means, resulting in a score for the sentences. I'm not sure how mathematically sound this approach is, but I've seen it done in other places (like python's gensim)....

cosine-similarity,word2vec,sentence-similarity

Cosine measures the angle between two vectors and does not take the length of either vector into account. When you divide by the length of the phrase, you are just shortening the vector, not changing its angular position. So your results look correct to me.