Algorithm to generate numerical concept hierarchy

Maybe you need a clustering algorithm?

Quoting from the link:

Cluster analysis or clustering is the assignment of a set of observations into subsets (called clusters) so that observations in the same cluster are similar in some sense. Clustering is a method of unsupervised learning, and a common technique for statistical data analysis used in many fields

Jenks Natural Breaks is a very efficient single dimension clustering scheme: http://www.spatialanalysisonline.com/OUTPUT/html/Univariateclassificationschemes.html#_Ref116892931

As comments have noted, this is very similar to k-means. However, I've found it even easier to implement, particularly the variation found in Borden Dent's Cartography: http://www.amazon.com/Cartography-Thematic-Borden-D-Dent/dp/0697384950

I think you're looking for something akin to data discretization that's fairly common in AI to convert continuous data (or discrete data with such a large number of classes as to be unwieldy) into discrete classes.

I know Weka uses Fayyad & Irani's MDL Method as well as Kononeko's MDL method, I'll see if I can dig up some references.