(Thus , where p is the parent of c.) Like USP, OntoUSP imposes local normalization constraints that enable closed-form estimation of the optimal parameters and likelihood.
using m-estimation, the optimal w c,v is log((m • e w p,v + n c,v )/(m + n c )), where p is the parent of c and n is the count.