Improved affinity graph based multi-document summarization

  • Authors:
  • Xiaojun Wan;Jianwu Yang

  • Affiliations:
  • Peking University, Beijing, China;Peking University, Beijing, China

  • Venue:
  • NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
  • Year:
  • 2006

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Abstract

This paper describes an affinity graph based approach to multi-document summarization. We incorporate a diffusion process to acquire semantic relationships between sentences, and then compute information richness of sentences by a graph rank algorithm on differentiated intra-document links and inter-document links between sentences. A greedy algorithm is employed to impose diversity penalty on sentences and the sentences with both high information richness and high information novelty are chosen into the summary. Experimental results on task 2 of DUC 2002 and task 2 of DUC 2004 demonstrate that the proposed approach outperforms existing state-of-the-art systems.