@InProceedings{che-EtAl:2017:RepEval,
  author    = {Che, Xiaoyin  and  Ring, Nico  and  Raschkowski, Willi  and  Yang, Haojin  and  Meinel, Christoph},
  title     = {Traversal-Free Word Vector Evaluation in Analogy Space},
  booktitle = {Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {11--15},
  abstract  = {In this paper, we propose an alternative evaluating metric for word analogy
	questions (A to B is as C to D) in word vector evaluation. Different from the
	traditional method which predicts the fourth word by the given three, we
	measure the similarity directly on the "relations" of two pairs of given words,
	just as shifting the relation vectors into a new analogy space. Cosine and
	Euclidean distances are then calculated as measurements. Observation and
	experiments shows the proposed analogy space evaluation could offer a more
	comprehensive evaluating result on word vectors with word analogy questions.
	Meanwhile, computational complexity are remarkably reduced by avoiding
	traversing the vocabulary.},
  url       = {http://www.aclweb.org/anthology/W17-5302}
}