QQ客服 官方微博 反馈留言

	The application of Kalman filter based human-computer learning model to Chinese word segmentation
	Zhu, Weimeng ; Sun, Ni ; Zou, Xiaojun ; Hu, Junfeng
	2013
英文摘要	This paper presents a human-computer interaction learning model for segmenting Chinese texts depending upon neither lexicon nor any annotated corpus. It enables users to add language knowledge to the system by directly intervening the segmentation process. Within limited times of user intervention, a segmentation result that fully matches the use (or with an accurate rate of 100% by manual judgement) is returned. A Kalman filter based model is adopted to learn and estimate the intention of users quickly and precisely from their interventions to reduce system prediction error hereafter. Experiments show that it achieves an encouraging performance in saving human effort and the segmenter with knowledge learned from users outperforms the baseline model by about 10% in segmenting homogenous texts. ? 2013 Springer-Verlag.; EI; 0
语种	英语
DOI标识	10.1007/978-3-642-37247-6_18
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/294538]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhu, Weimeng,Sun, Ni,Zou, Xiaojun,et al. The application of Kalman filter based human-computer learning model to Chinese word segmentation. 2013-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

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。