A Context-Sensitive Manifold Ranking Approach to Query-Focused Multi-document Summarization

  • Xiaoyan Cai
  • Wenjie Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6230)


Query-focused multi-document summarization aims to create a compressed summary biased to a given query. This paper presents a context-sensitive approach based on manifold ranking of sentences to this summarization task. The proposed context enhanced manifold ranking approach not only looks at the sentence itself, but also considers its surrounding contextual information. Compared to the existing manifold ranking approach which totally ignores the contextual information of a sentence, this approach can capture more additional relevant information which is especially necessary for formulating the relationships between short text snippets like sentences. Experiments are conducted on the DUC 2005 and DUC 2006 data sets and the ROUGE evaluation results demonstrate the advantages of the proposed approach.


Contextual Information Ranking Score Cosine Similarity Ranking Algorithm Affinity Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Xiaoyan Cai
    • 1
  • Wenjie Li
    • 1
  1. 1.Department of ComputingThe Hong Kong Polytechnic University 

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