Korean-Optimized Word Representations for Out-of-Vocabulary Problems Caused by Misspelling Using Sub-character Information

Author:

Kim Seonhghyun,Kim Jai-Eun,Hawang Seokhyun,Ivan Berlocher,Yang Seung-Won

Publisher

Springer International Publishing

Reference16 articles.

1. Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space, arXiv preprint arXiv:1301.3781 (2013)

2. Pennington, J., Socher, R., Manning, C.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1532–1543 (2014)

3. Sienčnik, S.K.: Adapting word2vec to named entity recognition. In: Proceedings of the 20th Nordic Conference of Computational Linguistics, Nodalida 2015, May 11–13, 2015, Vilnius, Lithuania, pp. 239–243. Linköping University Electronic Press (2015)

4. Hu, M., Peng, Y., Qiu, X.: Reinforced mnemonic reader for machine comprehension. CoRR, abs/1705.02798 (2017)

5. Wieting, J., Bansal, M., Gimpel, K., Livescu, K.: Charagram: embedding words and sentences via character n-grams, arXiv preprint arXiv:1607.02789 (2016)

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