QQ客服 官方微博 反馈留言

	A new event detection model based on term reweighting
	Zhang Kuo ; Li Juan-Zi ; Wu Gang ; Wang Ke-Hong
	2010-05-06 ; 2010-05-06
关键词	Practical Theoretical or Mathematical/ information resources information retrieval statistical analysis/ new event detection model term reweighting news stories training data linguistic data consortium TDT2 TDT3/ C7250R Information retrieval techniques C1140Z Other topics in statistics
中文摘要	New event detection (NED) is aimed at detecting from one or multiple streams of news stories the one being reported on a new event (i.e. not reported previously). Preliminary experiments show that terms of different types (e.g. noun and verb) have different effects for different classes of stories in determining whether or not two stories are on the same topic. Unfortunately, conventional approaches usually ignore the fact. This paper proposes a NED model utilizing two approaches to addressing the problem based on term reweighting. In the first approach, the paper proposes to employ statistics on training data to learn the model for each class of stories, and in the second, the paper proposes to adjust term weights dynamically based on previous story clusters. Experimental results on two linguistic data consortium (LDC) data sets: TDT2 and TDT3 show that both the proposed approaches can effectively improve the performance of NED task, compared to the baseline method and existing methods.
语种	中文 ; 中文
出版者	Science Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/10449]
专题	清华大学
推荐引用方式 GB/T 7714	Zhang Kuo,Li Juan-Zi,Wu Gang,et al. A new event detection model based on term reweighting[J],2010, 2010.
APA	Zhang Kuo,Li Juan-Zi,Wu Gang,&Wang Ke-Hong.(2010).A new event detection model based on term reweighting..
MLA	Zhang Kuo,et al."A new event detection model based on term reweighting".(2010).

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。