MWPRanker: An Expression Similarity Based Math Word Problem Retriever

被引:0
|
作者
Goel, Mayank [1 ]
Venktesh, V. [2 ]
Goyal, Vikram [2 ]
机构
[1] NSUT, Delhi, India
[2] Indraprastha Inst Informat Technol, Delhi, India
来源
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES: APPLIED DATA SCIENCE AND DEMO TRACK, ECML PKDD 2023, PT VII | 2023年 / 14175卷
关键词
D O I
10.1007/978-3-031-43430-3_33
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Math Word Problems (MWPs) in online assessments help test the ability of the learner to make critical inferences by interpreting the linguistic information in them. To test the mathematical reasoning capabilities of the learners, sometimes the problem is rephrased or the thematic setting of the original MWP is changed. Since manual identification of MWPs with similar problem models is cumbersome, we propose a tool in this work for MWP retrieval. We propose a hybrid approach to retrieve similar MWPs with the same problem model. In our work, the problem model refers to the sequence of operations to be performed to arrive at the solution. We demonstrate that our tool is useful for the mentioned tasks and better than semantic similarity-based approaches, which fail to capture the arithmetic and logical sequence of the MWPs. A demo of the tool can be found at https://www.youtube.com/watch?v=gSQWP3chFIs.
引用
收藏
页码:372 / 377
页数:6
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