Improved Affinity Graph Based Multi-Document Summarization

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.

• Publication year

  2006

• Venue

  North American Chapter of the Association for Computational Linguistics

• Publication date

  2006-06-04

• Fields of study

  Computer Science

• Identifiers
  DOI 10.3115/1614049.1614095
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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