Semantic Chunk Annotation for questions using Maximum Entropy

被引:0
|
作者
Fan, Shixi [1 ]
Zhang, Yaoyun [1 ]
Ng, Wing W. Y. [1 ]
Wang, Xuan [1 ]
Wang, Xiaolong [1 ]
机构
[1] Shenzhen Grad Sch, Harbin Inst Technol, Shenzhen, Peoples R China
关键词
Semantic Chunk Annotation; Q&A; Maximum Entropy; Mutual information;
D O I
10.1109/ICSMC.2008.4811317
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a ME (Maximum Entropy) model for Semantic Chunk Annotation in a Chinese Question and Answer (Q&A) system. The model was derived from a corpus of real world questions, which are collected from some discussion groups on the Internet. The questions are supposed to be answered by other people, so the questions are very complex. The semantic chunks were introduced. Feature for the model was described and MI (Mutual Information) was adopted for feature selection. The training data consists of 14000 sentences and the test data consists of 4000 sentences. The result: F-score is 90.68%.
引用
收藏
页码:450 / 454
页数:5
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