Beginner question, but I am a bit puzzled by this. Hope the answer to this question can benefit other beginners in NLP as well.
Here are some more details:
I know that you can compute sentence vectors from word vectors generated by word2vec. But what are the actual steps involved to make these sentence vectors. Can anyone provide a intuitive example and then some calculations to explain this process?
eg: Suppose I have a sentence with three words: Today is hot. And suppose these words have hypothetical vector values of: (1,2,3)(4,5,6)(7,8,9). Do I get the sentence vector by performing component-wise averaging of these word vectors? And what if the vectors are of different length eg: (1,2)(4,5,6)(7,8,9,23,76) what does the averaging process look like for these cases?