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	Joint learning of Chinese words, terms and keywords
	Cao, Ziqiang ; Li, Sujian ; Ji, Heng
	2014
英文摘要	Previous work often used a pipelined framework where Chinese word segmentation is followed by term extraction and keyword extraction. Such framework suffers from error propagation and is unable to leverage information in later modules for prior components. In this paper, we propose a four-level Dirichlet Process based model (DP-4) to jointly learn the word distributions from the corpus, domain and document levels simultaneously. Based on the DP-4 model, a sentence-wise Gibbs sampler is adopted to obtain proper segmentation results. Meanwhile, terms and keywords are acquired in the sampling process. Experimental results have shown the effectiveness of our method. ? 2014 Association for Computational Linguistics.; EI; 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/330024]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Cao, Ziqiang,Li, Sujian,Ji, Heng. Joint learning of Chinese words, terms and keywords. 2014-01-01.

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