Paper: Towards Coherent Multi-Document Summarization

ACL ID N13-1136
Title Towards Coherent Multi-Document Summarization
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

This paper presents G-FLOW, a novel system for coherent extractive multi-document sum- marization (MDS).1 Where previous work on MDS considered sentence selection and or- dering separately, G-FLOW introduces a joint model for selection and ordering that balances coherence and salience. G-FLOW?s core rep- resentation is a graph that approximates the discourse relations across sentences based on indicators including discourse cues, deverbal nouns, co-reference, and more. This graph en- ables G-FLOW to estimate the coherence of a candidate summary. We evaluate G-FLOW on Mechanical Turk, and find that it generates dramatically bet- ter summaries than an extractive summarizer based on a pipeline of state-of-the-art sentence selection and reordering components, under- scoring the value of our jo...