I am exploring different types of parse tree structures. The two widely known parse tree structures are a) Constituency based parse tree and b) Dependency based parse tree structures. I am able to use generate both types of parse tree structures using Stanford NLP package. However, I am not sure how to use these tree structures for my classification task. For e.g If I want to do sentiment analysis and want to categorize text into positive and negative classes, what features can I derive from parse tree structures for my classification task?
What features are generally used from Parse trees in classification process in NLP?
machine learning;nlp;feature selection;feature extraction