A Cluster-Sensitive Graph Model for Query-Oriented Multi-document Summarization

  • Furu Wei
  • Wenjie Li
  • Qin Lu
  • Yanxiang He
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4956)

Abstract

In this paper, we develop a novel cluster-sensitive graph model for query-oriented multi-document summarization. Upon it, an iterative algorithm, namely QoCsR, is built. As there is existence of natural clusters in the graph in the case that a document comprises a collection of sentences, we suggest distinguishing intra- and inter-document sentence relations in order to take into consideration the influence of cluster (i.e. document) global information on local sentence evaluation. In our model, five kinds of relations are involved among the three objects, i.e. document, sentence and query. Three of them are new and normally ignored in previous graph-based models. All these relations are then appropriately formulated in the QoCsR algorithm though in different ways. ROUGE evaluations shows that QoCsR can outperform the best DUC 2005 participating systems.

Keywords

Query-Oriented Summarization Multi-document Summarization Graph Model and Ranking Algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Furu Wei
    • 1
    • 2
  • Wenjie Li
    • 2
  • Qin Lu
    • 2
  • Yanxiang He
    • 1
  1. 1.Department of Computer Science and TechnologyWuhan UniversityChina
  2. 2.Department of ComputingThe Hong Kong Polytechnic UniversityHong Kong 

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