Modeling Multiple-Event Situations across News Articles

被引：0
|
作者：
Wagner, Earl J. [1 ]
Birnbaum, Larry [1 ]
Forbus, Kenneth D. [1 ]
机构：
[1] Northwestern Univ, Evanston, IL 60208 USA
来源：
K-CAP'09: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON KNOWLEDGE CAPTURE | 2009年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Readers interested in the context of an event covered in the news such as the dismissal of a lawsuit can benefit from easily finding out about the overall news situation, the legal trial, of which the event is a part. Guided by abstract models of news situation types such as legal trials, corporate acquisitions, and kidnappings, Brussell is a system that presents situation instances it creates by reading multiple articles about the specific events that comprise them. We discuss how these situation models are structured and how they drive the creation of particular instances.
引用
收藏
页码：207 / 208
页数：2
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