I am trying to develop a NLU (natural language understanding) engine which interprets human language utterance to intent and slots. After some searching, I found this very useful question for NLU novice like me: How to proceed with NLP task for recognizing intent and slots
In the answer, @darshan says:
...use a classifier to do the same using feature vector formulated from the input sentence.
I know that after transforming the sentence to a feature vector will be very useful for classification task. But how should we get such a feature vector?
For instance, the sentences:
What's the weather today?
What's it like out?
How's the weather? all should be classified to a
weather_query intent. But how to make these sentences into numerical feature vectors?