This paper has described using a domainindependent document modeling approach of avoiding low-content syntax words in an NLP task where high-content semantic words should be the principal focus.
we have shown that we can increase summarization performance by modeling the document set probability distribution using a hybrid LDA-HMM content and syntax model.