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AIRS
2010
Springer

Re-ranking Summaries Based on Cross-Document Information Extraction

9 years 7 months ago
Re-ranking Summaries Based on Cross-Document Information Extraction
This paper describes a novel approach of improving multi-document summarization based on cross-document information extraction (IE). We describe a method to automatically incorporate IE results into sentence ranking. Experiments have shown our integration methods can significantly improve a high-performing multi-document summarization system, according to the ROUGE-2 and ROUGE-SU4 metrics (7.38%% relative improvement on ROUGE-2 recall), and the generated summaries are preferred by human subjects (0.78 higher TAC Content score and 0.11 higher Readability/Fluency score).
Heng Ji, Juan Liu, Benoît Favre, Daniel Gill
Added 28 Feb 2011
Updated 28 Feb 2011
Type Journal
Year 2010
Where AIRS
Authors Heng Ji, Juan Liu, Benoît Favre, Daniel Gillick, Dilek Z. Hakkani-Tür
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