I have previously used Explicit Semantic Analysis (ESA) algorithm for individual word similarity calculations. ESA uses as a basis the text of Wikipedia entries and its ontology as a source and worked quite OK.

Do you / does anyone know if there is an easy way to use word2vec to compare similarities of two different documents (think of TF-IDF & cosine similarity)? It is stated on the page that "The linearity of the vector operations seems to weakly hold also for the addition of several vectors, so it is possible to add several word or phrase vectors to form representation of short sentences [2]", but the referenced paper has not yet been published.

It would be super interesting if there was a simple way to compare the similarities of two documents using something like this.