@inproceedings{3c18bd8cb98341fa9f56f5b8d25a4d0b,
title = "Exploiting word internal structures for generic Chinese sentence representation",
abstract = "We introduce a novel mixed character-word architecture to improve Chinese sentence representations, by utilizing rich semantic information of word internal structures. Our architecture uses two key strategies. The first is a mask gate on characters, learning the relation among characters in a word. The second is a max-pooling operation on words, adaptively finding the optimal mixture of the atomic and compositional word representations. Finally, the proposed architecture is applied to various sentence composition models, which achieves substantial performance gains over baseline models on sentence similarity task.",
author = "Shaonan Wang and Jiajun Zhang and Chengqing Zong",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics.; 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 ; Conference date: 09-09-2017 Through 11-09-2017",
year = "2017",
month = sep,
doi = "10.18653/v1/d17-1029",
language = "English",
series = "EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "298--303",
editor = "Martha Palmer and Rebecca Hwa and Sebastian Riedel",
booktitle = "EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings",
address = "United States",
}