Corpus ID: 1541076

Portuguese Word Embeddings: Evaluating on Word Analogies and Natural Language Tasks

@article{Hartmann2017PortugueseWE,
  title={Portuguese Word Embeddings: Evaluating on Word Analogies and Natural Language Tasks},
  author={Nathan Hartmann and Erick Rocha Fonseca and Christopher Shulby and Marcos Vin{\'i}cius Treviso and J{\'e}ssica S. Rodrigues and Sandra M. Alu{\'i}sio},
  journal={ArXiv},
  year={2017},
  volume={abs/1708.06025}
}
  • Nathan Hartmann, Erick Rocha Fonseca, +3 authors Sandra M. Aluísio
  • Published in STIL 2017
  • Computer Science
  • ArXiv
  • Word embeddings have been found to provide meaningful representations for words in an efficient way; therefore, they have become common in Natural Language Processing sys- tems. [...] Key Method We trained 31 word embedding models using FastText, GloVe, Wang2Vec and Word2Vec. We evaluated them intrinsically on syntactic and semantic analogies and extrinsically on POS tagging and sentence semantic similarity tasks. The obtained results suggest that word analogies are not appropriate for word embedding evaluation…Expand Abstract

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