@InProceedings{wang-he:2016:COLING,
  author    = {Wang, Chengyu  and  He, Xiaofeng},
  title     = {Chinese Hypernym-Hyponym Extraction from User Generated Categories},
  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     = {1350--1361},
  abstract  = {Hypernym-hyponym (“is-a”) relations are key components in taxonomies,
	object hierarchies and knowledge graphs. While there is abundant research on
	is-a relation extraction in English, it still remains a challenge to identify
	such relations from Chinese knowledge sources accurately due to the flexibility
	of language expression. In this paper, we introduce a weakly supervised
	framework to extract Chinese is-a relations from user generated categories. It
	employs piecewise linear projection models trained on a Chinese taxonomy and an
	iterative learning algorithm to update models incrementally. A pattern-based
	relation selection method is proposed to prevent “semantic drift” in the
	learning process using bi-criteria optimization. Experimental results
	illustrate that the proposed approach outperforms state-of-the-art methods.},
  url       = {http://aclweb.org/anthology/C16-1128}
}