Tech Report CS-96-37
Expected-frequency interpolation is a technique for improving the performance of deleted interpolation smoothing. It allows a system to make finer-grained estimates of how often one would expect to see a particular combination of events than is possible with traditional frequency interpolation. This allows the system to better weigh the emphasis given to the various probability distributions being mixed. We show that more traditional frequency interpolation, based solely on the frequency of conditioning events, can lead to some anomalous results. We then show that while the equations for expected-frequency interpolation are not exact, they are close, depending on how well some seemingly reasonable assumptions hold. We then present an experiment in which the introduction of expected-frequency interpolation to a statistical parsing system improved performance by .4% with essentially no extra work, and essentially no change in the workings of the system. We also note that even before the change, the system in question was the top performer at its task, so a .4% improvement was well worth obtaining.