CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
Integrating Generative and Discriminative Character-Based Models for Chinese Word Segmentation
Wang, Kun1; Zong, Chengqing1; Su, Keh-Yih2
2012-06
发表期刊ACM Transactions on Asian Language Information Processing (TALIP)
卷号11期号:2页码:7:1-7:41
摘要
Among statistical approaches to Chinese word segmentation, the word-based n-gram (generative) model and the character-based tagging (discriminative) model are two dominant approaches in the literature. The former gives excellent performance for the in-vocabulary (IV) words; however, it handles out-of-vocabulary(OOV) words poorly. On the other hand, though the latter is more robust for OOV words, it fails to deliver satisfactory performance for IV words. These two approaches behave differently due to the unit they use(word vs. character) and the model form they adopt (generative vs. discriminative). In general, characterbased approaches are more robust than word-based ones, as the vocabulary of characters is a closed set;and discriminative models are more robust than generative ones, since they can flexibly include all kinds of available information, such as future context. This article first proposes a character-based n-gram model to enhance the robustness of the generative approach. Then the proposed generative model is further integrated with the character-based discriminative model to take advantage of both approaches. Our experiments show that this integrated approach outperforms all the existing approaches reported in the literature. Afterwards, a complete and detailed
error analysis is conducted. Since a significant portion of the critical errors is related to numerical/foreign strings, character-type information is then incorporated into the model to further improve its performance. Last, the proposed integrated approach is tested on cross-domain corpora, and
关键词Chinese Word Segmentation
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12364
专题模式识别国家重点实验室_自然语言处理
通讯作者Wang, Kun
作者单位1.中国科学院自动化研究所
2.Behavior Design Corporation
推荐引用方式
GB/T 7714
Wang, Kun,Zong, Chengqing,Su, Keh-Yih. Integrating Generative and Discriminative Character-Based Models for Chinese Word Segmentation[J]. ACM Transactions on Asian Language Information Processing (TALIP),2012,11(2):7:1-7:41.
APA Wang, Kun,Zong, Chengqing,&Su, Keh-Yih.(2012).Integrating Generative and Discriminative Character-Based Models for Chinese Word Segmentation.ACM Transactions on Asian Language Information Processing (TALIP),11(2),7:1-7:41.
MLA Wang, Kun,et al."Integrating Generative and Discriminative Character-Based Models for Chinese Word Segmentation".ACM Transactions on Asian Language Information Processing (TALIP) 11.2(2012):7:1-7:41.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
2012.06 ACM TALIP K.(790KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Wang, Kun]的文章
[Zong, Chengqing]的文章
[Su, Keh-Yih]的文章
百度学术
百度学术中相似的文章
[Wang, Kun]的文章
[Zong, Chengqing]的文章
[Su, Keh-Yih]的文章
必应学术
必应学术中相似的文章
[Wang, Kun]的文章
[Zong, Chengqing]的文章
[Su, Keh-Yih]的文章
相关权益政策
暂无数据
收藏/分享
文件名: 2012.06 ACM TALIP K.Wang.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。