Event classification based on maximum entropy model

被引：0
|
作者：
Yu J.-D. [1 ]
Li X.-Y. [1 ]
Fan X.-Z. [2 ]
Pang W.-B. [2 ]
机构：
[1] School of Computer and Information Engineering, Anyang Normal University
[2] School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, Haidian
来源：
Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China | 2010年 / 39卷 / 04期
关键词：
Event classification; Event information extraction; Event mention sentence; Maximum entropy model; Trigger;
D O I：
10.3969/j.issn.1001-0548.2010.04.030
中图分类号：
学科分类号：
摘要：
An approach based on maximum entropy model is proposed for event classification. This approach can classify the events by merging the features about trigger and context in event mention sentences. The key of the method is parameter estimation and feature selection, which are discussed in detail. IIS algorithm is employed for parameter estimation and incremental method is used for feature selection. Experiments are performed on management succession, meeting, terror attack, judicial adjudicate, and natural disaster in the People Daily corpus. The results show that the method can achieve much better performance than the traditional approach.
引用
收藏
页码：612 / 616
页数：4
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