After training a doc2vec network can you only compare word vectors with each other and doc vectors with each other? Or does it also make sense to compare word vectors with doc vectors? Well, of course assuming that the dimensionality of the doc vector is the same as for the word vector (as for instance in a neural network that sums all word and doc vectors instead of concatenating them for classification).
For instance, if I have a high cosine similarity between a document vector and a particular word vector, does this imply that the document is somehow semantically similar to the word and vice versa? Thanks!