Semi-supervised Chinese Word Segmentation for CLP2012
He, Saike1; He, Nan2; Cen, Song-xiang1; Lu, Jun1
2012-12
Conference NameThe 2nd CIPS-SIGHAN Joint Conference on Chinese Language Processing (CLP-2012)
Source PublicationThe 2nd CIPS-SIGHAN Joint Conference on Chinese Language Processing (CLP-2012)
Pages79- 84
Conference Date2012-12-20 ~ 2012-12-21
Conference PlaceTianjin, China
AbstractChinese word segmentation (CWS) lays the essential foundation for Mandarin Chinese analysis. However, its performance is always limited by the identification of unknown words, especially for short text such as Microblog. While local context are helpless in handling unknown words, global context do manifest enough contextual information, and could be used to guide CWS process. Based on this motivation, in this paper, we report our attempt toward building an integrated model in semi-supervised manner. Considering the complexity of model, we design a strategy to manipulate global and local contextual information asynchronously. Though the coverage of unknown words by such integrated model is still small, official results from CLP2012 present promising result.
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Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10783
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorHe, Saike
Affiliation1.State Key Laboratory of Management and Control for Complex Systems Institute of Automation
2.Nuance Software Technology (Beijing) Co., Ltd.
Recommended Citation
GB/T 7714
He, Saike,He, Nan,Cen, Song-xiang,et al. Semi-supervised Chinese Word Segmentation for CLP2012[C],2012:79- 84.
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