@InProceedings{mathew-EtAl:2017:TextGraphs-11,
  author    = {Mathew, Binny  and  Maity, Suman Kalyan  and  Sarkar, Pratip  and  Mukherjee, Animesh  and  Goyal, Pawan},
  title     = {Adapting predominant and novel sense discovery algorithms for identifying corpus-specific sense differences},
  booktitle = {Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for Natural Language Processing},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {11--20},
  abstract  = {Word senses are not static and may have temporal, spatial or corpus-specific
	scopes. Identifying such scopes might benefit the existing WSD systems largely.
	In this paper, while studying corpus specific word senses, we adapt three
	existing predominant and novel-sense discovery algorithms to identify these
	corpus-specific senses. We make use of text data available in the form of
	millions of digitized books and newspaper archives as two different sources of
	corpora and propose automated methods to identify corpus-specific word senses
	at various time points. We conduct an extensive and thorough human judgement
	experiment to rigorously evaluate and compare the performance of these
	approaches. Post adaptation, the output of the three algorithms are in the same
	format and the accuracy results are also comparable, with roughly 45-60% of the
	reported corpus-specific senses being judged as genuine.},
  url       = {http://www.aclweb.org/anthology/W17-2402}
}