Previous studies have shown that the topic representation captured by topic models is useful for summarization (Nenkova and McKeown 2012).
there are two different purposes of using topic models in existing summarization systems: (1) to separate summary-worthy content and noncontent background (general information) (Daumé and Marcu 2006;Haghighi and Vanderwende 2009; Ç elikyilmaz and Hakkani-Tür 2010), and (2) to cluster sentences or documents into topics, with summaries then generated from each topic cluster for minimizing content redundancy (Salton et al.