Dimensionality reduction aids term co-occurrence based multi-document summarization

  • Authors:
  • Ben Hachey;Gabriel Murray;David Reitter

  • Affiliations:
  • University of Edinburgh, Edinburgh;University of Edinburgh, Edinburgh;University of Edinburgh, Edinburgh

  • Venue:
  • SumQA '06 Proceedings of the Workshop on Task-Focused Summarization and Question Answering
  • Year:
  • 2006
  • Automatic summarization

    HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts of ACL 2011

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Abstract

A key task in an extraction system for query-oriented multi-document summarisation, necessary for computing relevance and redundancy, is modelling text semantics. In the Embra system, we use a representation derived from the singular value decomposition of a term co-occurrence matrix. We present methods to show the reliability of performance improvements. We find that Embra performs better with dimensionality reduction.