{A {\TeX}-oriented research topic: Synthetic analysis on mathematical
 expressions and natural language}
{Takuto Asakura}
{Since mathematical expressions play fundamental roles in Science,
Technology, Engineering and Mathematics (\acro{STEM}) documents, it is
beneficial to extract meanings from formulae. Such extraction enables us
to construct databases of mathematical knowledge, search for formulae,
and develop a system that generates executable codes automatically.

{\TeX} is widely used to write \acro{STEM} documents and provides us
with a way to represent \emph{meanings} of elements in formulae in
{\TeX} by macros. As a simple example, we can define a macro\\
\verb|\def\inverse#1{#1^{-1}}|,\\ and use it as \verb|$\inverse{A}$| in
documents to make it clear that the expression means ``the inverse of
matrix~$A$'' rather than ``value~$A$ to the power of $-1$''. Using such
meaningful representations is useful in practice for maintaining
document sources, as well as converting {\TeX} sources to other formal
formats such as first-order logic and content markup in \MathML.
However, this manner is optional and not forced by {\TeX}. As a result,
many authors neglect it and write messy formulae in {\TeX} documents
(even with wrong markup).

To make it possible to associate elements in formulae and their meanings
automatically instead of requiring it of authors, recently I began
research on detecting or disambiguating the meaning for each element in
formulae by conducting synthetic analyses on mathematical expressions
and natural language text. In this presentation, I will show the goal of
my research, the approach I'm taking, and the current status of the
work.}