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2018 | OriginalPaper | Buchkapitel

Neural Domain Adaptation with Contextualized Character Embedding for Chinese Word Segmentation

verfasst von : Zuyi Bao, Si Li, Sheng Gao, Weiran Xu

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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Abstract

There has a large scale annotated newswire data for Chinese word segmentation. However, some research proves that the performance of the segmenter has significant decrease when applying the model trained on the newswire to other domain, such as patent and literature. The same character appeared in different words may be in different position and with different meaning. In this paper, we introduce contextualized character embedding to neural domain adaptation for Chinese word segmentation. The contextualized character embedding aims to capture the useful dimension in embedding for target domain. The experiment results show that the proposed method achieves competitive performance with previous Chinese word segmentation domain adaptation methods.

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We try to weight the target domains data more, but no significant improvement is observed.

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Titel: Neural Domain Adaptation with Contextualized Character Embedding for Chinese Word Segmentation
verfasst von: Zuyi Bao
Si Li
Sheng Gao
Weiran Xu
Verlag: Springer International Publishing
Buch: Natural Language Processing and Chinese Computing
Print ISBN: 978-3-319-73617-4

Electronic ISBN: 978-3-319-73618-1

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-73618-1_35

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