@InProceedings{wang-he-zhou:2017:EMNLP2017,
  author    = {Wang, Chengyu  and  He, Xiaofeng  and  Zhou, Aoying},
  title     = {A Short Survey on Taxonomy Learning from Text Corpora: Issues, Resources and Recent Advances},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {1190--1203},
  abstract  = {A taxonomy is a semantic hierarchy, consisting of concepts linked by is-a
	relations. While a large number of taxonomies have been constructed from
	human-compiled resources (e.g., Wikipedia), learning taxonomies from text
	corpora has received a growing interest and is essential for long-tailed and
	domain-specific knowledge acquisition. In this paper, we overview recent
	advances on taxonomy construction from free texts, reorganizing relevant
	subtasks into a complete framework. We also overview resources for evaluation
	and discuss challenges for future research.},
  url       = {https://www.aclweb.org/anthology/D17-1123}
}