Multi-document Summarization via Budgeted Maximization of Submodular Functions

We treat the text summarization problem as maximizing a submodular function under a budget constraint. We show, both theoretically and empirically, a modified greedy algorithm can efficiently solve the budgeted submodular maximization problem near-optimally, and we derive new approximation bounds in doing so. Experiments on DUC'04 task show that our approach is superior to the bestperforming method from the DUC'04 evaluation on ROUGE-1 scores.

• Type: Journal
• Year: 2010
• Where: NAACL
• Authors: Hui Lin, Jeff Bilmes
• Keywords: Computational Linguistics, Modified Greedy Algorithm, NAACL 2010, Submodular Maximization Problem, Text Summarization Problem