@InProceedings{luce-yu-hsieh:2016:CogALex-V,
  author    = {Luce, Kanan  and  Yu, Jiaxing  and  HSIEH, Shu-Kai},
  title     = {CogALex-V Shared Task: LOPE},
  booktitle = {Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {110--113},
  abstract  = {Automatic discovery of semantically-related words is one of the most important
	NLP tasks, and has great impact on the theoretical psycholinguistic modeling of
	the mental lexicon. In this shared task, we employ the word embeddings model to
	testify two thoughts explicitly or implicitly assumed by the NLP community:
	(1). Word embedding models can reflect syntagmatic similarities in usage
	between words to distances in projected vector space. (2). Word embedding
	models can reflect paradigmatic relationships between words.},
  url       = {http://aclweb.org/anthology/W16-5315}
}