Adversarial Multi-Criteria Learning for Chinese Word Segmentation
Published in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017
Recommended citation: Xinchi Chen, Zhan Shi, Xipeng Qiu, Xuanjing Huang: Adversarial Multi-Criteria Learning for Chinese Word Segmentation. ACL (1) 2017: 1193-1203 http://xuanjing-huang.github.io/files/cws.pdf
Different linguistic perspectives causes many diverse segmentation criteria for Chinese word segmentation (CWS). Most existing methods focus on improve the performance for each single criterion. However, it is interesting to exploit these different criteria and mining their common underlying knowledge. In this paper, we propose adversarial multi-criteria learning for CWS by integrating shared knowledge from multiple heterogeneous segmentation criteria. Experiments on eight corpora with heterogeneous segmentation criteria show that the performance of each corpus obtains a significant improvement, compared to single-criterion learning.