@InProceedings{dufter-EtAl:2018:Long,
  author    = {Dufter, Philipp  and  Zhao, Mengjie  and  Schmitt, Martin  and  Fraser, Alexander  and  Schütze, Hinrich},
  title     = {Embedding Learning Through Multilingual Concept Induction},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {1520--1530},
  abstract  = {We present a new method for estimating vector space representations of words: embedding learning by concept induction. We test this method on a highly parallel corpus and learn semantic representations of words in 1259 different languages in a single common space. An extensive experimental evaluation on crosslingual word similarity and sentiment analysis indicates that concept-based multilingual embedding learning performs better than previous approaches.},
  url       = {http://www.aclweb.org/anthology/P18-1141}
}