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	Distinguishing Specific and Daily Topics
	Ge, Tao ; Pei, Wenzhe ; Chang, Baobao ; Sui, Zhifang
	2015
关键词	specific and daily topics numeric features Bayesian model mixture of Poisson distribution
英文摘要	The task of distinguishing specific and daily topics is useful in many applications such as event chronicle and timeline generation, and cross-document event coreference resolution. In this paper, we investigate several numeric features that describe useful statistical information for this task, and propose a novel Bayesian model for distinguishing specific and daily topics from a collection of documents based on documents' content. The proposed Bayesian model exploits mixture of Poisson distributions for modeling probability distributions of the numeric features. The experimental results show that our approach is promising to solve this problem.; EI; CPCI-S(ISTP); getao@pku.edu.cn; peiwenzhe@pku.edu.cn; chbb@pku.edu.cn; szf@pku.edu.cn; 80-91; 9313
语种	英语
出处	WEB TECHNOLOGIES AND APPLICATIONS (APWEB 2015)
DOI标识	10.1007/978-3-319-25255-1_7
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436989]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Ge, Tao,Pei, Wenzhe,Chang, Baobao,et al. Distinguishing Specific and Daily Topics. 2015-01-01.

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