Abstract

Classical multi-document summaries focus on the common topics of a document set and omit distinctive themes particular to a single document—thereby often suppressing precisely that kind of information a user might need for a specific task. This can be avoided through advanced multi-document summaries that take a user's context and history into account, by delivering focused, contrastive, or update summaries. To facilitate the generation of these different summaries, we propose to generate all types from a single data structure, topic clusters, which provide for an abstract representation of a set of documents. Evaluations carried out on five years' worth of data from the DUC summarization competition prove the feasibility of this approach.

Reference

René Witte and Sabine Bergler. Next-Generation Summarization: Contrastive, Focused, and Update Summaries. International Conference on Recent Advances in Natural Language Processing (RANLP 2007), September 27-29, 2007, Borovets, Bulgaria.


Bibtex entry (also for download):

@InProceedings{WiBe07b,
  author =       {Ren{\'{e}} Witte and Sabine Bergler},
  title =        {{Next-Generation Summarization: 
                  Contrastive, Focused, and Update Summaries}},
  booktitle =    {International Conference on Recent Advances 
                  in Natural Language Processing (RANLP 2007)},
  year =         {2007},
  address =      {Borovets, Bulgaria},
  month =        {September 27--29},
  url   =        {http://rene-witte.net/next-generation-summarization}
}

You can also visit the conference website, which comes with lots of pictures...

Download

Our paper: 157_witte.pdf
MD5 checksum: 9d921a1616571cebc89a5f174f6bdd01

Copyright © 2007 René Witte and Sabine Bergler