1. Proc. of ACL;M Baroni,2014
2. From Frequency to Meaning: Vector Space Models of Semantics;PD Turney;Journal of Aritificial Intelligence Research,2010
3. Proc. of EMNLP;J Pennington,2014
4. Mikolov T, Chen K, Dean J. Efficient estimation of word representation in vector space. In: Proc. of International Conference on Learning Representations; 2013.
5. Ling W, Dyer C, Black AW, Trancoso I. Two/Too Simple Adaptations of Word2Vec for Syntax Problems. In: Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Denver, Colorado: Association for Computational Linguistics; 2015. p. 1299–1304. Available from: http://www.aclweb.org/anthology/N15-1142.