MWPRanker: An Expression Similarity Based Math Word Problem Retriever

Autor:	Goel, Mayank, V, Venktesh, Goyal, Vikram
Rok vydání:	2023
Předmět:	Computer Science - Information Retrieval Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	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 Comment: Accepted to ECML-PKDD 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2307.01240 Zobrazit plný text záznamu View this record from Arxiv