Classification of MathML Expressions Using Multilayer Perceptron

Abstract

MathML consists of two sets of elements: Presentation Markup and Content Markup. The former is more widely used to display math expressions in Web pages, while the latter is more suited to the calculation of math expressions. In this paper, we consider classifying math expressions in Presentation Markup. In general, a math expression in Presentation Markup cannot be uniquely converted into the corresponding expression in Content Markup. If the class of a given math expression can be identified automatically, such conversions can be done more appropriately. Moreover, identifying the class of a given math expression is useful for text-to-speech of math expression. In this paper, we propose a method for classifying math expressions in Presentation Markup by using a kind of deep learning; multilayer perceptron. Experimental results show that our method classifies math expressions with high accuracy.