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	Discriminative learning with natural annotations: Word segmentation as a case study
	JiangWenbin ; SunMeng ; Lü ; , Yajuan ; YangYating ; LiuQun
	2013
会议名称	51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
会议日期	August 4, 2013 - August 9, 2013
会议地点	Sofia, Bulgaria
页码	761-769
中文摘要	Structural information in web text provides natural annotations for NLP problems such as word segmentation and parsing. In this paper we propose a discriminative learning algorithm to take advantage of the linguistic knowledge in large amounts of natural annotations on the Internet. It utilizes the Internet as an external corpus with massive (although slight and sparse) natural annotations, and enables a classifier to evolve on the large-scaled and real-time updated web text. With Chinese word segmentation as a case study, experiments show that the segmenter enhanced with the Chinese wikipedia achieves significant improvement on a series of testing sets from different domains, even with a single classifier and local features.
收录类别	EI
会议录出版地	Association for Computational Linguistics (ACL)
语种	英语
ISBN号	9781937284503
内容类型	会议论文
源URL	[http://ir.xjipc.cas.cn/handle/365002/3616]
专题	新疆理化技术研究所_多语种信息技术研究室
推荐引用方式 GB/T 7714	JiangWenbin,SunMeng,Lü,et al. Discriminative learning with natural annotations: Word segmentation as a case study[C]. 见:51st Annual Meeting of the Association for Computational Linguistics, ACL 2013. Sofia, Bulgaria. August 4, 2013 - August 9, 2013.

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