This is a brief summary of paper for me to study and arrange for Word-Context Character Embeddings for Chinese Word Segmentation (Zhou et al., EMNLP 2017) I read and studied.
This paper is a research ralted to chinese segmenataion for cross domain.
They also used label embedding to use segmentation label information in the pre-training of character embedding
The model below is the baseline for Chinese Word segmenatation task they used.
They are inspired by skip-gram embedding model for pre-trainig of word-context character embedding.
Like image below, in order to train word-context character embedding, they used the context of character with the window size c, together with their corresponding segment labels.
Note(Abstract):
Neural parsers have benefited from automatically labeled data via dependencycontext word embeddings. They investigate training character embeddings on a word-based context in a similar way.
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The paper: Word-Context Character Embeddings for Chinese Word Segmentation (Zhou et al., EMNLP 2017)
The paper: Word-Context Character Embeddings for Chinese Word Segmentation (Zhou et al., EMNLP 2017)
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