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Most previous studies on meeting summarization have focused on extractive summarization. In this paper, we investigate if we can apply sentence compression to extractive summaries to generate abstractive summaries. We use different compression algorithms, including integer linear programming with an additional step of filler phrase detection, a noisychannel approach using Markovization formulation of grammar rules, as well as human compressed sentences. Our experiments on the ICSI meeting corpus show that when compared to the abstractive summaries, using sentence compression on the extractive summaries improves their ROUGE scores; however, the best performance is still quite low, suggesting the need of language generation for abstractive summarization.
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Liu et al. (2009) studied this question.