@InProceedings{chen-sun:2017:starSEM,
  author    = {Chen, Ao  and  Sun, Maosong},
  title     = {Domain-Specific New Words Detection in Chinese},
  booktitle = {Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {44--53},
  abstract  = {With the explosive growth of Internet, more and more domain-specific
	environments appear, such as forums, blogs, MOOCs and etc. Domain-specific
	words appear in these areas and always play a critical role in the
	domain-specific NLP tasks. This paper aims at extracting Chinese
	domain-specific new words automatically. The extraction of domain-specific new
	words has two parts including both new words in this domain and the especially
	important words. In this work, we propose a joint statistical model to perform
	these two works simultaneously. Compared to traditional new words detection
	models, our model doesn't need handcraft features which are labor intensive.
	Experimental results demonstrate that our joint model achieves a better
	performance compared with the state-of-the-art methods.},
  url       = {http://www.aclweb.org/anthology/S17-1005}
}