@InProceedings{ge-EtAl:2016:COLING,
  author    = {Ge, Tao  and  Cui, Lei  and  Chang, Baobao  and  Sui, Zhifang  and  Zhou, Ming},
  title     = {Event Detection with Burst Information Networks},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {3276--3286},
  abstract  = {Retrospective event detection is an important task for discovering previously
	unidentified events in a text stream. In this paper, we propose two fast
	centroid-aware event detection models based on a novel text stream
	representation -- Burst Information Networks (BINets) for addressing the
	challenge. The BINets are time-aware, efficient and can be easily analyzed for
	identifying key information (centroids). These advantages allow the BINet-based
	approaches to achieve the state-of-the-art performance on multiple datasets,
	demonstrating the efficacy of BINets for the task of event detection.
	Author{4}{Affiliation}},
  url       = {http://aclweb.org/anthology/C16-1309}
}