  Both supervised learning methods and LDA based topic model have been
successfully applied in the field of query focused multi-document
summarization. In this paper, we propose a novel supervised approach that can
incorporate rich sentence features into Bayesian topic models in a principled
way, thus taking advantages of both topic model and feature based supervised
learning methods. Experiments on TAC2008 and TAC2009 demonstrate the
effectiveness of our approach.
