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).

• Type: Journal
• Year: 2010
• Where: AIRS
• Authors: Heng Ji, Juan Liu, Benoît Favre, Daniel Gillick, Dilek Z. Hakkani-Tür
• Keywords: AIRS 2010, Cross-document Information Extraction, Information Technology, Multi-document Summarization, Relative Improvement