Is there any advanced collocation tool based on NLP+DL? I am not native English speaker and often times I use Ozdic to find the correct word choice. It's good overall but its database is quite limited. I think a tool based on Word2Vec should be able to do a great job for finding collocations/cooccurance. 


  With skip-grams, given a window size of n words around a word w, word2vec predicts contextual words c; i.e. in the notation of probability p(c|w). Conversely, CBOW predicts the current word, given the context in the window, p(w|c).


I am looking for a tool that takes a sentence with a blank spot as input and gives alternative options for the blank spot as an output.
You are describing the "Language Modeling" problem in NLP. Language modeling finds the probability distribution over sequences of words - given the words I have seen so far, what are the most likely words that will come next or are missing.

word2vec can find reasonable collocations/cooccurrence for individual words. However, word2vec will do a poor job with sentence completion because it does not model grammatical dependencies.

You can find a word2vec nearest individual word demo here.