Using thematic information in statistical headline generation

  • Authors:
  • Stephen Wan;Mark Dras;Cécile Paris;Robert Dale

  • Affiliations:
  • Macquarie University, Sydney, Australia;Macquarie University, Sydney, Australia;CSIRO Mathematical and Information Sciences, Sydney, Australia;Macquarie University, Sydney, Australia

  • Venue:
  • MultiSumQA '03 Proceedings of the ACL 2003 workshop on Multilingual summarization and question answering - Volume 12
  • Year:
  • 2003

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Abstract

We explore the problem of single sentence summarisation. In the news domain, such a summary might resemble a headline. The headline generation system we present uses Singular Value Decomposition (SVD) to guide the generation of a headline towards the theme that best represents the document to be summarised. In doing so, the intuition is that the generated summary will more accurately reflect the content of the source document. This paper presents SVD as an alternative method to determine if a word is a suitable candidate for inclusion in the headline. The results of a recall based evaluation comparing three different strategies to word selection, indicate that thematic information does help improve recall.