Clause-level Relationship-aware Math Word Problems Solver
文献类型:期刊论文
作者 | Chang-Yang Wu1; Xin Lin1; Zhen-Ya Huang1; Yu Yin1; Jia-Yu Liu1; Qi Liu1,2![]() ![]() |
刊名 | Machine Intelligence Research
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出版日期 | 2022 |
卷号 | 19期号:5页码:425-438 |
关键词 | Artificial intelligence (AI) artificial neural network (ANN) computational mathematics machine intelligence machine learning |
ISSN号 | 2731-538X |
DOI | 10.1007/s11633-022-1351-2 |
英文摘要 | Automatically solving math word problems, which involves comprehension, cognition, and reasoning, is a crucial issue in artificial intelligence research. Existing math word problem solvers mainly work on word-level relationship extraction and the generation of expression solutions while lacking consideration of the clause-level relationship. To this end, inspired by the theory of two levels of process in comprehension, we propose a novel clause-level relationship-aware math solver (CLRSolver) to mimic the process of human comprehension from lower level to higher level. Specifically, in the lower-level processes, we split problems into clauses according to their natural division and learn their semantics. In the higher-level processes, following human′s multi-view understanding of clause-level relationships, we first apply a CNN-based module to learn the dependency relationships between clauses from word relevance in a local view. Then, we propose two novel relationship-aware mechanisms to learn dependency relationships from the clause semantics in a global view. Next, we enhance the representation of clauses based on the learned clause-level dependency relationships. In expression generation, we develop a tree-based decoder to generate the mathematical expression. We conduct extensive experiments on two datasets, where the results demonstrate the superiority of our framework. |
源URL | [http://ir.ia.ac.cn/handle/173211/55954] ![]() |
专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
作者单位 | 1.Anhui Province Key Laboratory of Big Data Analysis and Application, School of Data Science, University of Science and Technology of China, Hefei 230026, China 2.Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China 3.Laboratory of Mathematical Engineering and Advanced Computing, Information Engineering University, Zhengzhou 450001, China |
推荐引用方式 GB/T 7714 | Chang-Yang Wu,Xin Lin,Zhen-Ya Huang,et al. Clause-level Relationship-aware Math Word Problems Solver[J]. Machine Intelligence Research,2022,19(5):425-438. |
APA | Chang-Yang Wu.,Xin Lin.,Zhen-Ya Huang.,Yu Yin.,Jia-Yu Liu.,...&Gang Zhou.(2022).Clause-level Relationship-aware Math Word Problems Solver.Machine Intelligence Research,19(5),425-438. |
MLA | Chang-Yang Wu,et al."Clause-level Relationship-aware Math Word Problems Solver".Machine Intelligence Research 19.5(2022):425-438. |
入库方式: OAI收割
来源:自动化研究所
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