Character-to-Word Attention for Word Segmentation
Citations Over Time
Abstract
Although limited effort has been devoted to exploring neural models in Japanese word segmentation, much effort has been actively applied to Chinese word segmentation because of the ability to minimize effort in feature engineering. In this work, we propose a character-based neural model that makes joint use of word information useful for disambiguating word boundaries. For each character in a sentence, our model uses an attention mechanism to estimate the importance of multiple candidate words that contain the character. Experimental results show that learning attention to proper words leads to accurate segmentations and that our model achieves better performance than existing statistical and neural models on both in-domain and cross-domain Japanese word segmentation datasets.
Related Papers
- → Character, Action, Incident(2011)2 cited
- A Small Character, A Great Spirit(2003)
- A Discussion of Protruding the News Character,Pertinent Character and Regional Character of Supplement——Based on the Cases of Chaozhou Daily(2010)
- A Comment on the Official Seal Character Quality of "Shuowen Jiezi" (Remarks on the Character Structure)(2005)
- Briefly on the Change of Environment to Character(2007)