@InProceedings{li-bing-lam:2017:FrontiersSummarization,
  author    = {Li, Piji  and  Bing, Lidong  and  Lam, Wai},
  title     = {Reader-Aware Multi-Document Summarization: An Enhanced Model and The First Dataset},
  booktitle = {Proceedings of the Workshop on New Frontiers in Summarization},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {91--99},
  abstract  = {We investigate the problem of reader-aware multi-document summarization
	(RA-MDS) and introduce a new dataset for this problem. To tackle RA-MDS, we
	extend a variational auto-encodes (VAEs) based MDS framework by jointly
	considering news documents and reader comments. To conduct evaluation for
	summarization performance, we prepare a new dataset. We describe the methods
	for data collection, aspect annotation, and summary writing as well as
	scrutinizing by experts. Experimental results show that reader comments can
	improve the summarization performance, which also demonstrates the usefulness
	of the proposed dataset.},
  url       = {http://www.aclweb.org/anthology/W17-4512}
}