QQ客服 官方微博 反馈留言

	Event Recognition from News Webpages through Latent Ingredients Extraction
	Yan, Rui ; Li, Yu ; Zhang, Yan ; Li, Xiaoming
	2010
关键词	Event Recognition Latent ingredient Segmentation SEGMENTATION MARKERS PASSAGES TEXT
英文摘要	We investigate the novel problem of event recognition from news webpages. "Events" are basic text units containing news elements. We observe that a news article is always constituted by more than one event, namely Latent Ingredients (Lis) which form the whole document. Event recognition aims to mine these Latent Ingredients out. Researchers have tackled related problems before, such as discourse analysis and text segmentation, with different goals and methods. The challenge is to detect event boundaries from plain contexts accurately and the boundary decision is affected by multiple features. Event recognition can be beneficial for topic detection with finer granularity and better accuracy. In this paper, we present two novel event recognition models based on Us extraction and exploit a set of useful features consisting of context similarity, distance restriction, entity influence from thesaurus and temporal proximity. We conduct thorough experiments with two real datasets and the promising results indicate the effectiveness of these approaches.; Computer Science, Information Systems; Computer Science, Software Engineering; Computer Science, Theory & Methods; EI; CPCI-S(ISTP); 4
语种	英语
DOI标识	10.1007/978-3-642-17187-1_47
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/293047]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yan, Rui,Li, Yu,Zhang, Yan,et al. Event Recognition from News Webpages through Latent Ingredients Extraction. 2010-01-01.

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。