方法证据记录
FastText
FastText is a word embedding and text classification framework developed by Facebook AI Research (Joulin, Bojanowski, Grave, and Mikolov, 2016–2017) that represents each word as the sum of its character n-gram vectors, allowing it to construct meaningful representations for unseen and morphologically rich words and to perform near state-of-the-art text classification orders of magnitude faster than deep neural network alternatives.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
FastText: Subword-Level Word Embeddings and Efficient Text Classification
分类方法记录 · ml-model / deep-learning
- Joulin, A., Grave, E., Bojanowski, P. & Mikolov, T. (2017). Bag of Tricks for Efficient Text Classification. In Proceedings of EACL 2017, Short Papers, pp. 427–431. ACL. · DOI 10.18653/v1/e17-2068
- Bojanowski, P., Grave, E., Joulin, A. & Mikolov, T. (2017). Enriching Word Vectors with Subword Information. Transactions of the Association for Computational Linguistics, 5, 135–146. · DOI 10.1162/tacl_a_00051
- Goldberg, Y. (2017). Neural Network Methods for Natural Language Processing. Morgan & Claypool Publishers. · ISBN 978-1-62705-298-6
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