A hybrid approach for semantic enrichment of MathML mathematical expressions
This addresses the challenge of accurately interpreting mathematical expressions in documents for applications like search and accessibility, but it is an incremental improvement.
The paper tackles the problem of semantic enrichment of MathML mathematical expressions by combining statistical machine translation with disambiguation using surrounding text, achieving improvements over prior systems.
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.