Cognitive search operation

1. A computer-implementable method for performing a cognitive search operation comprising:

receiving training data, the training data comprising information based upon user interaction with cognitive attributes;

performing a machine learning operation on the training data;

performing a cognitive learning operation via a cognitive inference and learning system using the training data, the cognitive learning operation implementing a cognitive learning technique according to a cognitive learning framework, the cognitive learning framework comprising a plurality of cognitive learning styles and a plurality of cognitive learning categories, each of the plurality of cognitive learning styles comprising a generalized learning approach implemented by the cognitive inference and learning system to perform the cognitive learning operation, each of the plurality of cognitive learning categories referring to a source of information used by the cognitive inference and learning system when performing the cognitive learning operation, an individual cognitive learning technique being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the cognitive learning operation applying the cognitive learning technique via the machine learning operation to generate a cognitive learning result;

generating a cognitive profile based upon the cognitive learning result generated by performing the machine learning operation; and,

performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user; and wherein

the plurality of cognitive learning techniques comprising a direct correlations cognitive learning technique, an explicit likes/dislikes cognitive learning technique, a patterns and concepts cognitive learning technique, a behavior cognitive learning technique, a concept entailment cognitive learning technique, and a contextual recommendation cognitive learning technique, the direct correlations cognitive learning technique being associated with a declared learning style and bounded by a data-based cognitive learning category, the explicit likes/dislikes cognitive learning technique being associated with the declared learning style and bounded by an interaction-based cognitive learning category, the patterns and concepts cognitive learning technique being associated with an observed learning style and bounded by the data-based cognitive learning category, the behavior cognitive learning technique being associated with the observed learning style and bounded by the interaction-based cognitive learning category, the concept entailment cognitive learning technique being associated with an inferred learning style and bounded by the data-based cognitive learning category, and the contextual recommendation cognitive learning technique being associated with the inferred learning style and bounded by the interaction-based cognitive learning category.

2. The method of claim 1 , wherein:

the results specific to the user are further refined based upon terms used when performing the cognitive search operation.

3. The method of claim 2 , wherein:

a second user having a second cognitive profile and performing a search using the terms used when performing the cognitive search operation would return cognitive results specific to the second cognitive profile.

4. The method of claim 1 , wherein:

the machine learning operation comprises a ranked insight model operation, the ranked insight operation comprising a factor-needs operation.

5. The method of claim 1 , wherein:

the machine learning operation comprises a hierarchical topic model operation, the hierarchical topic model operation comprises a domain topic abstraction operation and a hierarchical topic operation.

6. The method of claim 1 , wherein:

the cognitive profile is continuously updated based upon at least one of a plurality of feedback information sources, the feedback information sources comprising information based upon feedback from interactions between the user and the cognitive insight and learning system, information from a query submitted by the user to the cognitive insight and learning system, information from external input data, information from a user navigating a hierarchical topic model and information received from a training system.

7. A system comprising:

a processor;

a data bus coupled to the processor; and

a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for:

receiving training data, the training data comprising information based upon user interaction with cognitive attributes;

performing a machine learning operation on the training data;

performing a cognitive learning operation via a cognitive inference and learning system using the training data, the cognitive learning operation implementing a cognitive learning technique according to a cognitive learning framework, the cognitive learning framework comprising a plurality of cognitive learning styles and a plurality of cognitive learning categories, each of the plurality of cognitive learning styles comprising a generalized learning approach implemented by the cognitive inference and learning system to perform the cognitive learning operation, each of the plurality of cognitive learning categories referring to a source of information used by the cognitive inference and learning system when performing the cognitive learning operation, an individual cognitive learning technique being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the cognitive learning operation applying the cognitive learning technique via the machine learning operation to generate a cognitive learning result;

generating a cognitive profile based upon the cognitive learning result generated by performing the machine learning operation; and,

performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user; and wherein

the plurality of cognitive learning techniques comprising a direct correlations cognitive learning technique, an explicit likes/dislikes cognitive learning technique, a patterns and concepts cognitive learning technique, a behavior cognitive learning technique, a concept entailment cognitive learning technique, and a contextual recommendation cognitive learning technique, the direct correlations cognitive learning technique being associated with a declared learning style and bounded by a data-based cognitive learning category, the explicit likes/dislikes cognitive learning technique being associated with the declared learning style and bounded by an interaction-based cognitive learning category, the patterns and concepts cognitive learning technique being associated with an observed learning style and bounded by the data-based cognitive learning category, the behavior cognitive learning technique being associated with the observed learning style and bounded by the interaction-based cognitive learning category, the concept entailment cognitive learning technique being associated with an inferred learning style and bounded by the data-based cognitive learning category, and the contextual recommendation cognitive learning technique being associated with the inferred learning style and bounded by the interaction-based cognitive learning category.

8. The system of claim 7 , wherein:

the results specific to the user are further refined based upon terms used when performing the cognitive search operation.

9. The system of claim 8 , wherein:

a second user having a second cognitive profile and performing a search using the terms used when performing the cognitive search operation would return cognitive results specific to the second cognitive profile.

10. The system of claim 7 , wherein:

the plurality of machine learning operation comprise a ranked insight model operation, the ranked insight operation comprising a factor-needs operation.

11. The system of claim 7 , wherein:

the machine learning operation comprises a hierarchical topic model operation, the hierarchical topic model operation comprises a domain topic abstraction operation and a hierarchical topic operation.

12. The system of claim 7 , wherein:

the cognitive profile is continuously updated based upon at least one of a plurality of feedback information sources, the feedback information sources comprising information based upon feedback from interactions between the user and the cognitive insight and learning system, information from a query submitted by the user to the cognitive insight and learning system, information from external input data, information from a user navigating a hierarchical topic model and information received from a training system.

13. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

receiving training data, the training data comprising information based upon user interaction with cognitive attributes;

performing a machine learning operation on the training data;

performing a cognitive learning operation via a cognitive inference and learning system using the training data, the cognitive learning operation implementing a cognitive learning technique according to a cognitive learning framework, the cognitive learning framework comprising a plurality of cognitive learning styles and a plurality of cognitive learning categories, each of the plurality of cognitive learning styles comprising a generalized learning approach implemented by the cognitive inference and learning system to perform the cognitive learning operation, each of the plurality of cognitive learning categories referring to a source of information used by the cognitive inference and learning system when performing the cognitive learning operation, an individual cognitive learning technique being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the cognitive learning operation applying the cognitive learning technique via the machine learning operation to generate a cognitive learning result;

generating a cognitive profile based upon the cognitive learning result generated by performing the machine learning operation; and,

performing a cognitive search operation on a corpus of content based upon the cognitive profile, the cognitive search operation returning cognitive results specific to the cognitive profile of the user; and wherein

the plurality of cognitive learning techniques comprising a direct correlations cognitive learning technique, an explicit likes/dislikes cognitive learning technique, a patterns and concepts cognitive learning technique, a behavior cognitive learning technique, a concept entailment cognitive learning technique, and a contextual recommendation cognitive learning technique, the direct correlations cognitive learning technique being associated with a declared learning style and bounded by a data-based cognitive learning category, the explicit likes/dislikes cognitive learning technique being associated with the declared learning style and bounded by an interaction-based cognitive learning category, the patterns and concepts cognitive learning technique being associated with an observed learning style and bounded by the data-based cognitive learning category, the behavior cognitive learning technique being associated with the observed learning style and bounded by the interaction-based cognitive learning category, the concept entailment cognitive learning technique being associated with an inferred learning style and bounded by the data-based cognitive learning category, and the contextual recommendation cognitive learning technique being associated with the inferred learning style and bounded by the interaction-based cognitive learning category.

14. The non-transitory, computer-readable storage medium of claim 13 , wherein:

the results specific to the user are further refined based upon terms used when performing the cognitive search operation.

15. The non-transitory, computer-readable storage medium of claim 14 , wherein:

a second user having a second cognitive profile and performing a search using the terms used when performing the cognitive search operation would return cognitive results specific to the second cognitive profile.

16. The non-transitory, computer-readable storage medium of claim 13 , wherein:

the plurality of machine learning operation comprise a ranked insight model operation, the ranked insight operation comprising a factor-needs operation.

17. The non-transitory, computer-readable storage medium of claim 13 , wherein:

the machine learning operation comprises a hierarchical topic model operation, the hierarchical topic model operation comprises a domain topic abstraction operation and a hierarchical topic operation.

18. The non-transitory, computer-readable storage medium of claim 13 , wherein:

the cognitive profile is continuously updated based upon at least one of a plurality of feedback information sources, the feedback information sources comprising information based upon feedback from interactions between the user and the cognitive insight and learning system, information from a query submitted by the user to the cognitive insight and learning system, information from external input data, information from a user navigating a hierarchical topic model and information received from a training system.

19. The non-transitory, computer-readable storage medium of claim 13 , wherein the computer executable instructions are deployable to a client system from a server system at a remote location.

20. The non-transitory, computer-readable storage medium of claim 13 , wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.