This work aims at helping students understand complex mathematical expressions that appear in academic documents such as research papers. To this end, we focus on subexpressions of an expression given as a query, and try to annotate them using information about known similar expressions, while most existing approaches tend to find out an expression similar to the whole of a query. Assuming that an expression is given in the form of Content Markup of MathML, we construct its DOM tree, and extract subtrees each of which corresponds to one of its subexpressions from the whole tree. Then, we search a database storing known expressions associated with their meta-data for ones similar to the subexpressions. To evaluate the usefulness of our approach, we conducted experiments using actual mathematical expressions collected from a web site and a mathematical textbook, and confirmed that considering subexpressions can bring on more information helpful for better understanding of a given query expression compared to annotating itself.