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?


1 Answer 1


I suggest you build a classifier for each intent and then use that to find any given intent in a sentence. For starters, work using a rule based system such as using a keywords or regex. Then once you've enough sentences go forward with the machine learning classifier and keep improving it.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.