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Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov, Kai Chen, Greg Corrado et al., 2013. arXiv.
Introduces the continuous bag-of-words and skip-gram models, the basis of word2vec, for learning word vectors efficiently from large corpora.
What it's used for here
Listed in the inductive methods survey's references on word embeddings.
Cited by on this site 1 record
1 methods surveys
SRCInductive methods
Cite it
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient Estimation of Word Representations in Vector Space. arXiv. https://arxiv.org/abs/1301.3781
@article{mikolov2013efficient,
author = {Mikolov, Tomas and Chen, Kai and Corrado, Greg and Dean, Jeffrey},
title = {Efficient Estimation of Word Representations in Vector Space},
journal = {arXiv},
year = {2013},
url = {https://arxiv.org/abs/1301.3781}
}TY - GEN TI - Efficient Estimation of Word Representations in Vector Space AU - Mikolov, Tomas AU - Chen, Kai AU - Corrado, Greg AU - Dean, Jeffrey PY - 2013 JO - arXiv UR - https://arxiv.org/abs/1301.3781 ER -
Mikolov, Tomas et al.. “Efficient Estimation of Word Representations in Vector Space.” arXiv (2013).