Manual and automatic evaluation of summaries

  • Authors:
  • Chin-Yew Lin;Eduard Hovy

  • Affiliations:
  • USC Information Sciences Institute, Marina del Rey, CA;USC Information Sciences Institute, Marina del Rey, CA

  • Venue:
  • AS '02 Proceedings of the ACL-02 Workshop on Automatic Summarization - Volume 4
  • Year:
  • 2002

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Abstract

In this paper we discuss manual and automatic evaluations of summaries using data from the Document Understanding Conference 2001 (DUC-2001). We first show the instability of the manual evaluation. Specifically, the low inter-human agreement indicates that more reference summaries are needed. To investigate the feasibility of automated summary evaluation based on the recent BLEU method from machine translation, we use accumulative n-gram overlap scores between system and human summaries. The initial results provide encouraging correlations with human judgments, based on the Spearman rank-order correlation coefficient. However, relative ranking of systems needs to take into account the instability.