• Computer Science
• Published in
  Transactions of the…
  2016
• DOI:10.1162/tacl_a_00051

Enriching Word Vectors with Subword Information

@article{Bojanowski2016EnrichingWV,
  title={Enriching Word Vectors with Subword Information},
  author={Piotr Bojanowski and Edouard Grave and Armand Joulin and Tomas Mikolov},
  journal={Transactions of the Association for Computational Linguistics},
  year={2016},
  volume={5},
  pages={135-146}
}

• Piotr Bojanowski, Edouard Grave, +1 author Tomas Mikolov

Continuous word representations, trained on large unlabeled corpora are useful for many natural language processing tasks. Popular models that learn such representations ignore the morphology of words, by assigning a distinct vector to each word. This is a limitation, especially for languages with large vocabularies and many rare words. In this paper, we propose a new approach based on the skipgram model, where each word is represented as a bag of character n-grams. A vector representation is… CONTINUE READING

View on MIT Press

Open Access

Save to Library

Create Alert

Cite