大数据2025，Vol.11Issue(5)：34-47,14.DOI:10.11959/j.issn.2096-0271.2025057
基于对比学习的数学应用题求解方法研究
Study on solving math word problem based on contrastive learning
摘要
Abstract
The automatic solving of MWP not only provides students with accurate learning guidance but also helps alleviate teacher workload and promotes advancements of smart education.Existing MWP-solving methods face challenges in extracting deep semantic information and unifying the solutions for various types of MWP,and addressing the subtle differences in similar problems.To address these challenges,a general MWP solving model,BSCL,was proposed.Firstly,pre-trained language models were used to encode MWP in natural language form,employing contrastive learning methods to enhance the encoder's ability to understand different MWP types.Then,the model unified the decoding of various types of MWP and used a supervision task to ensure mathematical consistency between the problems and expressions.Extensive experiments on both Chinese and English datasets indicate that BSCL has the effectiveness and superiority in solving different types of MWP tasks.关键词
数学应用题/自然语言处理/对比学习Key words
math word problem/natural language processing/contrastive learning分类
信息技术与安全科学引用本文复制引用
张天成,王玉杨,张亦嘉,于明鹤,冷芳玲,于戈..基于对比学习的数学应用题求解方法研究[J].大数据,2025,11(5):34-47,14.基金项目
国家自然科学基金项目(No.62272093 （）
No.62372097 （）
No.62137001) The National Natural Science Foundation of China(No.62272093,No.62372097,No.62137001) （No.62272093,No.62372097,No.62137001）
