Multi-Document Summarization with Subjectivity Analysis

نویسندگان

  • Yohei Seki
  • Koji Eguchi
  • Noriko Kando
  • Masaki Aono
چکیده

In this paper, we present our team TUT/NII results at DUC 2005 and additional experiments on improving multi-document summarization. Summarization systems have typically focused on the factual aspect of information needs. Subjectivity analysis is another essential aspect for better understanding of information needs. Our approach is based on sentence extraction, weighted by sentence type annotation, and combined with polarity term frequencies. We selected 10 topics related to subjectivity with analysis of “narratives”, and investigated improvements of ROUGE (RecallOriented Understudy for Gisting Evaluation) and BE (Basic Elements) scores with our approach. In addition, the factual aspect of information needs was also investigated.

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تاریخ انتشار 2005