Chinese Comma Disambiguation in Math Word Problems Using SMOTE and Random Forests

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成果类型：

期刊论文

作者：

Qingtang Liu;Yunxiang Zheng;Jingxiu Huang;Linjing Wu

通讯作者：

Yunxiang Zheng<&wdkj&>Jingxiu Huang

作者机构：

Authors to whom correspondence should be addressed.

School of Information Technology in Education, South China Normal University, Guangzhou 510631, China

[Qingtang Liu; Linjing Wu] School of Educational Information Technology, Central China Normal University, Wuhan 430079, China

[Yunxiang Zheng; Jingxiu Huang] Authors to whom correspondence should be addressed.<&wdkj&>School of Information Technology in Education, South China Normal University, Guangzhou 510631, China

通讯机构：

[Yunxiang Zheng; Jingxiu Huang] A

Authors to whom correspondence should be addressed.<&wdkj&>School of Information Technology in Education, South China Normal University, Guangzhou 510631, China

语种：

英文

关键词：

comma disambiguation;feature engineering;hyperparameter tuning;imbalanced learning;natural language understanding;random forests

期刊：

ISSN：

2673-2688

年：

2021

卷：

期：

页码：

738-755

DOI：

10.3390/ai2040044

基金类别：

Conceptualization, Q.L.; methodology, J.H.; resources, L.W. and J.H.; writing—original draft preparation, J.H. and Q.L.; writing—review and editing, L.W. and Y.Z.; visualization, J.H.; supervision, Y.Z.; project administration, J.H.; funding acquisition, Q.L. All authors have read and agreed to the published version of the manuscript. This work was supported by China Postdoctoral Science Foundation under grant no. 2021M701273 and the National Natural Science Foundation of China under grant no. 61772012.

机构署名：

本校为其他机构

院系归属：

教育信息技术学院

摘要：

Natural language understanding technologies play an essential role in automatically solving math word problems. In the process of machine understanding Chinese math word problems, comma disambiguation, which is associated with a class imbalance binary learning problem, is addressed as a valuable instrument to transform the problem statement of math word problems into structured representation. Aiming to resolve this problem, we employed the synthetic minority oversampling technique (SMOTE) and random forests to comma classification after their hyperparameters were jointly optimized. We propose...

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Chinese Comma Disambiguation in Math Word Problems Using SMOTE and Random Forests

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