  We propose Text2Math, a model for semantically parsing text into math
expressions. The model can be used to solve different math related problems
including arithmetic word problems and equation parsing problems. Unlike
previous approaches, we tackle the problem from an end-to-end structured
prediction perspective where our algorithm aims to predict the complete math
expression at once as a tree structure, where minimal manual efforts are
involved in the process. Empirical results on benchmark datasets demonstrate
the efficacy of our approach.
