@InProceedings{polsley-jhunjhunwala-huang:2016:COLINGDEMO,
  author    = {Polsley, Seth  and  Jhunjhunwala, Pooja  and  Huang, Ruihong},
  title     = {CaseSummarizer: A System for Automated Summarization of Legal Texts},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {258--262},
  abstract  = {Attorneys, judges, and others in the justice system are constantly surrounded
	by large amounts of legal text, which can be difficult to manage across many
	cases. We present CaseSummarizer, a tool for automated text summarization of
	legal documents which uses standard summary methods based on word frequency
	augmented with additional domain-specific knowledge. Summaries are then
	provided through an informative interface with abbreviations, significance heat
	maps, and other flexible controls. It is evaluated using ROUGE and human
	scoring against several other summarization systems, including summary text and
	feedback provided by domain experts.},
  url       = {http://aclweb.org/anthology/C16-2054}
}