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Aspect-Based Personalized Text Summarization

  • Shlomo Berkovsky
  • Timothy Baldwin
  • Ingrid Zukerman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5149)

Abstract

This work investigates user attitudes towards personalized summaries generated from a coarse-grained user model based on document aspects. We explore user preferences for summaries at differing degrees of fit with their stated interests, the impact of length on user ratings, and the faithfulness of personalized and general summaries.

Keywords

User Model User Interest General Summary Baleen Whale Average Faithfulness 
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 2008

Authors and Affiliations

  • Shlomo Berkovsky
    • 1
  • Timothy Baldwin
    • 1
  • Ingrid Zukerman
    • 2
  1. 1.University of MelbourneAustralia
  2. 2.Monash UniversityAustralia

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