Given a sentence: "When I open the ?? door it starts heating automatically"
I would like to get the list of possible words in ?? with a probability.
The basic concept used in word2vec model is to "predict" a word given surrounding context.
Once the model is build, what is the right context vectors operation to perform my prediction task on new sentences?
Is it simply a linear sum?
model.most_similar(positive=['When','I','open','the','door','it','starts' , 'heating','automatically'])