3. The method of claim 2 , further comprising generating, by the computer, a master topic computer model comprising a first set of one or more term vectors identified in text of the document corpus upon determining the relationship of the corresponding term vectors from the plurality of co-occurring topics.
3. The method of claim 2 , further comprising generating, by the computer, a master topic computer model comprising a first set of one or more term vectors identified in text of the document corpus upon determining the relationship of the corresponding term vectors from the plurality of co-occurring topics. 7. The method of claim 3 , wherein the master topic computer model is a multi-component extension of a Latent Dirichlet Allocation (MC-LDA) topic model.