Exploiting Novelty, Coverage and Balance for Topic-Focused Multi-Document Summarization

Novelty, coverage and balance are important requirements in topic-focused summarization, which to a large extent de-termine the quality of a summary. In this paper, we pro-pose a novel method that incorporates these requirements into a sentence ranking probability model. It differs from the existing methods in that the novelty, coverage and bal-ance requirements are all modeled w.r.t. a given topic, so that summaries are highly relevant to the topic and at the same time comply with topic-aware novelty, coverage and balance. Experimental results on the DUC 2005, 2006 and 2007 benchmark data sets demonstrate the effectiveness of our method