@InProceedings{johnson-EtAl:2017:W17-55,
  author    = {Johnson, Jordon  and  Masrani, Vaden  and  Carenini, Giuseppe  and  Ng, Raymond},
  title     = {Generating and Evaluating Summaries for Partial Email Threads: Conversational Bayesian Surprise and Silver Standards},
  booktitle = {Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue},
  month     = {August},
  year      = {2017},
  address   = {Saarbrücken, Germany},
  publisher = {Association for Computational Linguistics},
  pages     = {263--272},
  abstract  = {We define and motivate the problem of summarizing partial email threads. This
	problem introduces the challenge of generating reference summaries for partial
	threads when human annotation is only available for the threads as a whole,
	particularly when the human-selected sentences are not uniformly distributed
	within the threads. We propose an oracular algorithm for generating these
	reference summaries with arbitrary length, and we are making the resulting
	dataset publicly available. In addition, we apply a recent unsupervised method
	based on Bayesian Surprise that incorporates background knowledge into partial
	thread summarization, extend it with conversational features, and modify the
	mechanism by which it handles redundancy. Experiments with our method indicate
	improved performance over the baseline for shorter partial threads; and our
	results suggest that the potential benefits of background knowledge to partial
	thread summarization should be further investigated with larger datasets.},
  url       = {http://aclweb.org/anthology/W17-5532}
}