SUTLER: Update Summarizer Based on Latent Topics

نویسندگان

  • Josef Steinberger
  • Karel Jezek
چکیده

This paper deals with our past and recent research in text summarization. We went from single-document summarization through multidocument summarization to update summarization. We describe the development of our summarizer which is based on latent semantic analysis (LSA). The classical LSA-based summarization model was improved by Iterative Residual Rescaling. We propose the update summarization component which determines the redundancy and novelty of each topic discovered by LSA. Moreover, we have modified the sentence selection component in order to prevent inner summary redundancy. The results of our first participation in TAC/DUC evaluation seem to be promising.

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تاریخ انتشار 2008