The past methods either only learn parameters with one or two levels (e.g., in hierarchical Bayes), or requires significant amount of computation (e.g., in EM and in L 1 -regularized maxent), while also typically assuming a given hierarchy.
ontoUSP has to both induce the hierarchy and populate it, with potentially many levels in the induced hierarchy, starting from raw text with little user supervision.