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We introduce a novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations.
Network structure and minimum degree
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Vladimir Batagelj and Matjaž Zaveršnik. 2002 · 2002
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A. Janin, D. Baron, J. Edwards, D. Ellis, D. Gelbart, N. Morgan, B. Peskin, T. Pfau, E. Shriberg, A. Stolcke, and C. Wooters. 2003 · 2003
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Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy. 2003 · 2003
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Iain McCowan, Jean Carletta, W Kraaij, S Ashby, S Bourban, M Flynn, M Guillemot, T Hain, J Kadlec, V Karaiskos, et al. 2005 · 2005
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Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
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Korbinian Riedhammer, Dan Gillick, Benoit Favre, and Dilek Hakkani-Tür. 2008 · 2008
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Nikhil Garg, Benoit Favre, Korbinian Reidhammer, and Dilek Hakkani-Tür. 2009 · 2009
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Katja Filippova. 2010 · 2010
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Identification of influential spreaders in complex networks
Maksim Kitsak, Lazaros K Gallos, Shlomo Havlin, Fredrik Liljeros, Lev Muchnik, H Eugene Stanley, and Hernán A Makse. 2010 · 2010
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Multi-document summarization via budgeted maximization of submodular functions
Abstractive meeting summarization with entailment and fusion
Yashar Mehdad, Giuseppe Carenini, Frank Tompa, and Raymond T. NG. 2013 · 2013
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François Rousseau and Michalis Vazirgiannis. 2013 · 2013
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Joonhyun Bae and Sangwook Kim. 2014 · 2014
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Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, and Kilian Q. Weinberger. 2015 · 2015
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A graph degeneracy-based approach to keyword extraction
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Submodularity in natural language processing: algorithms and applications
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Gowvis: A web application for graph-of-words-based text visualization and summarization
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