  Query Auto Completion (QAC) is among the most appealing features of a web
search engine. It helps users formulate queries quickly with less effort.
Although there has been much effort in this area for text, to the best of our
knowledge there is few work on mathematical formula auto completion. In this
paper, we implement 5 existing QAC methods on mathematical formula and evaluate
them on the NTCIR-12 MathIR task dataset. We report the efficiency of retrieved
results using Mean Reciprocal Rank (MRR) and Mean Average Precision(MAP). Our
study indicates that the Finite State Transducer outperforms other QAC models
with a MRR score of $0.642$.
