Cognitive session graphs including blockchains

1. A computer-implementable method for generating and using a cognitive session graph comprising:

receiving data from a blockchain data source, the blockchain data source providing blockchain data, the data comprising temporal attributes;

processing the data, the processing the data from the plurality of data sources performing data enriching to provide enriched data, the processing the data using the temporal attributes to correlate elements of the data with a time window;

providing the blockchain data to a cognitive inference and learning system, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph comprising an application cognitive graph, the application cognitive graph comprising a cognitive graph associated with a cognitive application, interactions between the cognitive application and the application cognitive graph being represented as a set of nodes in the cognitive graph;

generating the cognitive session graph, the cognitive session graph being associated with a session, the cognitive session graph comprising at least some enriched data, the session comprising a plurality of queries over a period of time, the plurality of queries being stored within the cognitive session graph associated with the session;

generating a weighted cognitive graph, a cognitive profile being defined by a set of nodes within the weighted cognitive graph, the cognitive profile being defined by a set of attributes that are respectively associated with a set of corresponding nodes in the weighted cognitive graph, the set of attributes including an attribute weight, the attribute weight representing a relevance between two attributes of the set of attributes;

performing a cognitive machine learning operation via the cognitive inference and learning system using the blockchain data, the cognitive machine learning operation implementing a cognitive learning technique from a plurality of cognitive learning techniques 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 of the plurality of cognitive learning techniques being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the cognitive machine learning operation applying the cognitive learning technique via a machine learning algorithm to generate a cognitive learning result;

associating a cognitive blockchain with the cognitive session graph; and,

updating a knowledge model using the cognitive learning result and the cognitive session graph, the updating being performed via the cognitive platform of the cognitive inference and learning system.

2. The method of claim 1 , wherein:

the session is related to at least one of a user, group of users, theme, topic, issue, question, intent, goal, objective, task, assignment, process, situation, requirement, condition, responsibility, location, period of time and a block in a blockchain.

3. The method of claim 1 , further comprising:

processing the cognitive session graph and the cognitive blockchain to provide a cognitive insight, the cognitive insight being related to the session.

4. The method of claim 3 , further comprising:

processing the data from the plurality of data sources, the processing the data from the plurality of data sources performing data enriching to provide second enriched data;

generating a second cognitive session graph, the second cognitive session graph being associated with a second session, the second cognitive session graph comprising at least some of the second enriched data; and,

processing the second cognitive session graph to provide a second cognitive insight, the second cognitive insight being related to the second session.

5. The method of claim 4 , wherein:

the session and the second session are associated with a single user;

the session and the second session correspond to a first purpose and a second purpose, respectively; and,

the cognitive insight and the second cognitive insight are related to the first purpose and the second purpose, respectively.

6. The method of claim 1 , wherein:

the cognitive session graph comprises a user query, the user query being represented as a node within the cognitive session graph; and

the node within the cognitive session graph is linked to a node within a universal cognitive graph.

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 data from a blockchain data source, the blockchain data source providing blockchain data, the data comprising temporal attributes;

processing the data, the processing the data from the plurality of data sources performing data enriching to provide enriched data, the processing the data using the temporal attributes to correlate elements of the data with a time window;

providing the blockchain data to a cognitive inference and learning system, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph comprising an application cognitive graph, the application cognitive graph comprising a cognitive graph associated with a cognitive application, interactions between the cognitive application and the application cognitive graph being represented as a set of nodes in the cognitive graph;

generating the cognitive session graph, the cognitive session graph being associated with a session, the cognitive session graph comprising at least some enriched data, the session comprising a plurality of queries over a period of time, the plurality of queries being stored within the cognitive session graph associated with the session;

generating a weighted cognitive graph, a cognitive profile being defined by a set of nodes within the weighted cognitive graph, the cognitive profile being defined by a set of attributes that are respectively associated with a set of corresponding nodes in the weighted cognitive graph, the set of attributes including an attribute weight, the attribute weight representing a relevance between two attributes of the set of attributes;

performing a cognitive machine learning operation via the cognitive inference and learning system using the blockchain data, the cognitive machine learning operation implementing a cognitive learning technique from a plurality of cognitive learning techniques 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 of the plurality of cognitive learning techniques being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the cognitive machine learning operation applying the cognitive learning technique via a machine learning algorithm to generate a cognitive learning result;

associating a cognitive blockchain with the cognitive session graph; and,

updating a knowledge model using the cognitive learning result and the cognitive session graph, the updating being performed via the cognitive platform of the cognitive inference and learning system.

8. The system of claim 7 , wherein:

the session is related to at least one of a user, group of users, theme, topic, issue, question, intent, goal, objective, task, assignment, process, situation, requirement, condition, responsibility, location, period of time and a block in a blockchain.

9. The system of claim 7 , wherein the instructions executable by the processor further comprise instructions for:

processing the cognitive session graph and the cognitive blockchain to provide a cognitive insight, the cognitive insight being related to the session.

10. The system of claim 9 , wherein:

processing the data from the plurality of data sources, the processing the data from the plurality of data sources performing data enriching to provide second enriched data;

generating a second cognitive session graph, the second cognitive session graph being associated with a second session, the second cognitive session graph comprising at least some of the second enriched data; and,

processing the second cognitive session graph to provide a second cognitive insight, the second cognitive insight being related to the second session.

11. The system of claim 10 , wherein:

the session and the second session are associated with a single user;

the session and the second session correspond to a first purpose and a second purpose, respectively; and,

the cognitive insight and the second cognitive insight are related to the first purpose and the second purpose, respectively.

12. The system of claim 7 , wherein:

the cognitive session graph comprises a user query, the user query being represented as a node within the cognitive session graph; and

the node within the cognitive session graph is linked to a node within a universal cognitive graph.

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

receiving data from a blockchain data source, the blockchain data source providing blockchain data, the data comprising temporal attributes;

processing the data, the processing the data from the plurality of data sources performing data enriching to provide enriched data, the processing the data using the temporal attributes to correlate elements of the data with a time window;

providing the blockchain data to a cognitive inference and learning system, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph comprising an application cognitive graph, the application cognitive graph comprising a cognitive graph associated with a cognitive application, interactions between the cognitive application and the application cognitive graph being represented as a set of nodes in the cognitive graph;

generating the cognitive session graph, the cognitive session graph being associated with a session, the cognitive session graph comprising at least some enriched data, the session comprising a plurality of queries over a period of time, the plurality of queries being stored within the cognitive session graph associated with the session;

generating a weighted cognitive graph, a cognitive profile being defined by a set of nodes within the weighted cognitive graph, the cognitive profile being defined by a set of attributes that are respectively associated with a set of corresponding nodes in the weighted cognitive graph, the set of attributes including an attribute weight, the attribute weight representing a relevance between two attributes of the set of attributes;

performing a cognitive machine learning operation via the cognitive inference and learning system using the blockchain data, the cognitive machine learning operation implementing a cognitive learning technique from a plurality of cognitive learning techniques 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 of the plurality of cognitive learning techniques being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the cognitive machine learning operation applying the cognitive learning technique via a machine learning algorithm to generate a cognitive learning result;

associating a cognitive blockchain with the cognitive session graph; and,

updating a knowledge model using the cognitive learning result and the cognitive session graph, the updating being performed via the cognitive platform of the cognitive inference and learning system.

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

the session is related to at least one of a user, group of users, theme, topic, issue, question, intent, goal, objective, task, assignment, process, situation, requirement, condition, responsibility, location, period of time and a block in a blockchain.

15. The non-transitory, computer-readable storage medium of claim 13 , wherein the instructions executable by the processor further comprise instructions for:

processing the cognitive session graph and the cognitive blockchain to provide a cognitive insight, the cognitive insight being related to the session.

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

processing the data from the plurality of data sources, the processing the data from the plurality of data sources performing data enriching to provide second enriched data;

generating a second cognitive session graph, the second cognitive session graph being associated with a second session, the second cognitive session graph comprising at least some of the second enriched data; and,

processing the second cognitive session graph to provide a second cognitive insight, the second cognitive insight being related to the second session.

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

the session and the second session are associated with a single user;

the session and the second session correspond to a first purpose and a second purpose, respectively; and,

the cognitive insight and the second cognitive insight are related to the first purpose and the second purpose, respectively.

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

the cognitive session graph comprises a user query, the user query being represented as a node within the cognitive session graph; and

the node within the cognitive session graph is linked to a node within a universal cognitive graph.

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.