This makes especially sense as we are dealing with 179 different datasets of different sizes, where a comparison of the top-k results with a fixed k is not meaningful (e.g., it makes a huge difference if the correct author is in the top-5 in a dataset containing 20 authors or in one containing 16,000 authors).
we experimented with the reduction rates 10-90%, 95%, and 99%, and measured the hit rate, i.e., the percentage of how often the correct author is still in the reduced candidate set.