Organizing data into taxonomies is a way to help users navigate large collections of information. Some of these collections are of relatively narrow interest and are used by trained specialists; others are for lay users to explore and take advantage of. This paper investigates the best manner to build hierarchical indexes automatically for the consumption of data collections by lay users. Its main contributions are in (1) applying a clear focus toward addressing the need of a non-specialist, untrained base of users (much of the previous work was aimed at the needs of specialists); (2) identifying through experimental trials several metrics useful in general for ranking competing algorithmic approaches; and (3) proposing novel criteria and algorithms that appear to perform statistically better than what was tried in the past.
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