7. The method as recited in claim 1 , further comprising generating a global conditional probability matrix comprising a primary set of terms defining a first dimension of the global conditional probability matrix and a secondary set of terms defining a second dimension of the global conditional probability matrix, wherein the primary set of terms comprises at least a portion of the major term set, the secondary set of terms comprises discriminatory features identified in a corpus of information, and entries in the global conditional probability matrix comprise the conditional probability that a document contains a term from the secondary set when it contains a term from the primary set.
9. The method as recited in claim 7 , wherein the global conditional probability matrix comprises an aggregate of partial conditional probability matrices from the plurality of processes.