15. The apparatus method as set forth in claim 11 , wherein the selecting of categorization labels includes: determining derived probability values for derived categories, each derived category corresponding to an ordered combination of categories from different categorization dimensions, the derived probability value for each derived category being determined based on the probability value of one of the categories of the ordered combination of categories weighted by the probability value of the other one of the categories of the ordered combination; and selecting an optimized derived category based on the derived probability values and selecting a categorization label respective to each categorization dimension that corresponds to the optimized derived category.
15. The apparatus method as set forth in claim 11 , wherein the selecting of categorization labels includes: determining derived probability values for derived categories, each derived category corresponding to an ordered combination of categories from different categorization dimensions, the derived probability value for each derived category being determined based on the probability value of one of the categories of the ordered combination of categories weighted by the probability value of the other one of the categories of the ordered combination; and selecting an optimized derived category based on the derived probability values and selecting a categorization label respective to each categorization dimension that corresponds to the optimized derived category. 17. The method as set forth in claim 15 , wherein the determining of derived probability values for derived categories employs an interdependency weighting factor associated with each derived category in performing the weighting.