Semantic Tagging of Mathematical Expressions
Pao-Yu Chien, Pu‐Jen Cheng · 2015
Semantic tagging of mathematical expressions (STME) gives semantic meanings to tokens in mathematical expressions. In this work, we propose a novel STME approach that relies on neither text along with expressions, nor labelled training data. Instead, our method only requires a mathematical grammar set. We point out that, besides the grammar of mathematics, the special property of variables and user habits of writing expressions help us understand the implicit intents of the user. We build a system that considers both restrictions from the grammar and variable properties, and then apply an unsupervised method to our probabilistic model to learn the user habits. To evaluate our system, we build large-scale training and test datasets automatically from a public math forum. The results demonstrate the significant improvement of our method, compared to the maximum-frequency baseline. We also create statistics to reveal the properties of mathematics language.