Character-to-Word Attention for Word Segmentation: Research Process
Author:
Affiliation:
1. National Institute of Information and Communications Technology
Publisher
Association for Natural Language Processing
Link
https://www.jstage.jst.go.jp/article/jnlp/28/2/28_688/_pdf
Reference7 articles.
1. Higashiyama, S., Utiyama, M., Matsumoto, Y., Watanabe, T., and Sumita, E. (2020a). “Auxiliary Lexicon Word Prediction for Cross-Domain Word Segmentation.” Journal of Natural Language Processing, 27 (3), pp. 573–598.
2. Higashiyama, S., Utiyama, M., Sumita, E., Ideuchi, M., Oida, Y., Sakamoto, Y., and Okada, I. (2019). “Incorporating Word Attention into Character-Based Word Segmentation.” In Proceedings of NAACL-HLT, pp. 2699–2709.
3. Higashiyama, S., Utiyama, M., Sumita, E., Ideuchi, M., Oida, Y., Sakamoto, Y., and Okada, I. (2020b). “Character-to-Word Attention for Word Segmentation.” Journal of Natural Language Processing, 27 (3), pp. 499–530.
4. Kitagawa, Y. and Komachi, M. (2018). “Long Short-term Memory for Japanese Word Segmentation.” In Proceedings of PACLIC, pp. 279–288.
5. Kudo, T. and Richardson, J. (2018). “SentencePiece: A Simple and Language Independent Subword Tokenizer and Detokenizer for Neural Text Processing.” In Proceedings of EMNLP, pp. 66–71.
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