@InProceedings{grishin:2018:S18-1,
  author    = {Grishin, Maxim},
  title     = {Igevorse at SemEval-2018 Task 10: Exploring an Impact of Word Embeddings Concatenation for Capturing Discriminative Attributes},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {995--998},
  abstract  = {This paper presents a comparison of several approaches for capturing discriminative attributes and considers an impact of concatenation of several word embeddings of different nature on the classification performance. A similarity-based method is proposed and compared with classical machine learning approaches. It is shown that this method outperforms others on all the considered word vector models and there is a performance increase when concatenated datasets are used.},
  url       = {http://www.aclweb.org/anthology/S18-1164}
}