Paper: A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization

ACL ID P13-1136
Title A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

We consider the problem of using sentence compression techniques to facilitate query- focused multi-document summarization. We present a sentence-compression-based frame- work for the task, and design a series of learning-based compression models built on parse trees. An innovative beam search de- coder is proposed to efficiently find highly probable compressions. Under this frame- work, we show how to integrate various in- dicative metrics such as linguistic motivation and query relevance into the compression pro- cess by deriving a novel formulation of a com- pression scoring function. Our best model achieves statistically significant improvement over the state-of-the-art systems on several metrics (e.g. 8.0% and 5.4% improvements in ROUGE-2 respectively) for the DUC 2006 and 2007 summar...