Word2Vec and Tf-idf how to combine them
Word2Vec algorithms (Skip Gram and CBOW) treat each word equally,
because their goal to compute word embeddings. The distinction
becomes important when one needs to work with sentences or document
embeddings; not all words equally represent the meaning of a
particular sentence. And here different weighting strategies are
applied, TF-IDF is one of those successful strategies.
At times, it does improve quality of inference, so combination is
worth a shot.
Glove is a Stanford baby, which has often proved to perform better. Can
read more about Glove against Word2Vec here, among many other
resources available online.