3. The method of claim 1 , further comprising training the deep question answering system to generate the machine learning concept model, wherein training the deep question answering system comprises: providing the deep question answering system with a sample case and a sample answer; identifying the first concept in the sample case; computing the concept matching score for the first concept in the sample case based on the sample answer; and including the concept matching score in the machine learning concept model.
3. The method of claim 1 , further comprising training the deep question answering system to generate the machine learning concept model, wherein training the deep question answering system comprises: providing the deep question answering system with a sample case and a sample answer; identifying the first concept in the sample case; computing the concept matching score for the first concept in the sample case based on the sample answer; and including the concept matching score in the machine learning concept model. 4. The method of claim 3 , wherein producing the machine learning concept model further comprises identifying a type of question included in the sample case, wherein the type of question includes the first concept, wherein the concept matching score is based a degree of relevancy for the first concept and the type of question.