A hybrid approach for semantic enrichment of MathML mathematical expressions

TL;DR

This paper introduces a hybrid method combining statistical machine translation and disambiguation to improve the semantic enrichment of MathML expressions, leveraging surrounding text for better accuracy.

Contribution

It presents a novel hybrid approach that integrates SVM-based disambiguation with statistical translation for enhanced MathML semantic enrichment.

Findings

System outperforms previous methods

Improved disambiguation accuracy

Enhanced semantic representation of MathML

Abstract

In this paper, we present a new approach to the semantic enrichment of mathematical expression problem. Our approach is a combination of statistical machine translation and disambiguation which makes use of surrounding text of the mathematical expressions. We first use Support Vector Machine classifier to disambiguate mathematical terms using both their presentation form and surrounding text. We then use the disambiguation result to enhance the semantic enrichment of a statistical-machine-translation-based system. Experimental results show that our system archives improvements over prior systems.