  We describe the Library Event Matching classification algorithm implemented
for use in the NOvA $\nu_\mu \rightarrow \nu_e$ oscillation measurement.
Library Event Matching, developed in a different form by the earlier MINOS
experiment, is a powerful approach in which input trial events are compared to
a large library of simulated events to find those that best match the input
event. A key feature of the algorithm is that the comparisons are based on all
the information available in the event, as opposed to higher-level derived
quantities. The final event classifier is formed by examining the details of
the best-matched library events. We discuss the concept, definition,
optimization, and broader applications of the algorithm as implemented here.
Library Event Matching is well-suited to the monolithic, segmented detectors of
NOvA and thus provides a powerful technique for event discrimination.
