Machine learning
FastText
FastText 是由 Facebook 人工智能研究实验室（Joulin, Bojanowski, Grave, and Mikolov, 2016–2017）开发的一个词嵌入和文本分类框架，它将每个词表示为其字符 n-gram 向量的总和，从而能够为未见过的和形态丰富的词构建有意义的表示，并以比深度神经网络替代方案快几个数量级的方式执行近乎最先进的文本分类。
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来源
- 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
如何引用本页
ScholarGate. (2026, June 3). FastText: Subword-Level Word Embeddings and Efficient Text Classification. ScholarGate. https://scholargate.app/zh/deep-learning/fasttext
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