Deep Neural Solver for Math Word Problems
Yan Wang, Xiaojiang Liu, Shuming Shi · 2017
This paper presents a deep neural solver to automatically solve math word problems.In contrast to previous statistical learning approaches, we directly translate math word problems to equation templates using a recurrent neural network (RNN) model, without sophisticated feature engineering.We further design a hybrid model that combines the RNN model and a similarity-based retrieval model to achieve additional performance improvement.Experiments conducted on a large dataset show that the RNN model and the hybrid model significantly outperform stateof-the-art statistical learning methods for math word problem solving. 1 We plan to make the dataset publicly available when the paper is published