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.
@article{arxiv.1606.07849,
title = {Focused Meeting Summarization via Unsupervised Relation Extraction},
author = {Lu Wang and Claire Cardie},
journal= {arXiv preprint arXiv:1606.07849},
year = {2016}
}