MWPRanker: An Expression Similarity Based Math Word Problem Retriever

TL;DR

This paper introduces MWPRanker, a hybrid retrieval tool that effectively finds similar math word problems by analyzing their problem models, outperforming semantic similarity methods in capturing arithmetic and logical sequences.

Contribution

The work presents a novel hybrid approach for MWP retrieval based on problem models, improving over existing semantic similarity techniques.

Findings

The tool accurately retrieves MWPs with similar problem models.

It outperforms semantic similarity-based approaches.

Demonstrated effectiveness through experimental results.

Abstract

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