1. A system for assessing the selectivity of categorization rules, the system comprising: a computer system including at least one processor, a non-transitory data storage medium interfaced with the at least one processor, and input/output facilities, the data storage medium containing instructions that, when executed by the at least one processor, implement: a categorization rule application engine configured to apply at least one categorization rule to a set of un-categorized objects to produce a categorization result set representing assignment of objects the set into at least two categories, the categorization rule application engine further configured to gather statistical information relating to the categorization result set based on properties of objects assigned to each of the at least two categories; a selectivity determination engine configured to assess a numerical selectivity score for the at least one categorization rule based on the statistical information, the numerical selectivity score representing an estimation of accuracy of the at least one categorization rule, wherein the selectivity determination engine applies at least one trained selectivity determination algorithm to produce the selectivity score; and an algorithm training engine configured to produce the at least one trained selectivity determination algorithm based on application of a plurality of specially-selected categorization rules to a set of pre-categorized training data, wherein the application of each one of the specially-selected categorization rules to the set of training data produces at least one uniform grouping of objects in which the objects all meet a predefined similarity criterion.