@InProceedings{wang-EtAl:2017:Long5,
  author    = {Wang, Chengyu  and  Yan, Junchi  and  Zhou, Aoying  and  He, Xiaofeng},
  title     = {Transductive Non-linear Learning for Chinese Hypernym Prediction},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1394--1404},
  abstract  = {Finding the correct hypernyms for entities is essential for taxonomy learning,
	fine-grained entity categorization, query understanding, etc. Due to the
	flexibility of the Chinese language, it is challenging to identify hypernyms
	in Chinese accurately. Rather than extracting hypernyms from texts, in this
	paper, we present a transductive learning approach to establish mappings from
	entities to hypernyms in the embedding space directly. It combines linear and
	non-linear embedding projection models, with the capacity of
	encoding arbitrary language-specific rules. Experiments on real-world datasets
	illustrate that our approach outperforms previous methods for Chinese hypernym
	prediction.},
  url       = {http://aclweb.org/anthology/P17-1128}
}