Abstractive Multi-Document Summarization via Phrase Selection and Merging

Understand

We propose an abstraction-based multi-document summarization framework that can construct new sentences by exploring more fine-grained syntactic units than sentences, namely, noun/verb phrases.

• Different from existing abstraction-based approaches, our method first constructs a pool of concepts and facts represented by phrases from the input documents.
• Then new sentences are generated by selecting and merging informative phrases to maximize the salience of phrases and meanwhile satisfy the sentence construction constraints.
• We employ integer linear optimization for conducting phrase selection and merging simultaneously in order to achieve the global optimal solution for a summary.