Focused meeting summarization via unsupervised relation extraction

  • Authors:
  • Lu Wang;Claire Cardie

  • Affiliations:
  • Cornell University, Ithaca, NY;Cornell University, Ithaca, NY

  • Venue:
  • SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present a novel unsupervised framework for focused meeting summarization that views the problem as an instance of relation extraction. We adapt an existing in-domain relation learner (Chen et al., 2011) by exploiting a set of task-specific constraints and features. We evaluate the approach on a decision summarization task and show that it outperforms unsupervised utterance-level extractive summarization baselines as well as an existing generic relation-extraction-based summarization method. Moreover, our approach produces summaries competitive with those generated by supervised methods in terms of the standard ROUGE score.