Travel-related cognitive profiles

1. A system comprising:

a processor; and

a non-transitory, computer-readable storage medium comprising instructions for: receiving streams of data from a plurality of data sources;

incorporating the data into a cognitive graph comprising a set of nodes

and edges

by incorporating one or more entities determined from data into the cognitive graph by incorporating one or more sub-graphs into the cognitive graph so that the cognitive graph includes at least one node representing those one or more entitles and one or more links between the at least one node representing those one or more entitles and one or more of the other set of nodes of the cognitive graph;

defining a first travel-related cognitive persona within the cognitive graph, the first travel-related cognitive persona corresponding to a first archetype user model, the first travel-related cognitive persona comprising a first sub-graph within the cognitive graph, the first sub-graph including a first set of nodes and first weighted edges between the first set of nodes in the cognitive graph;

defining a second travel-related cognitive persona within the cognitive graph, the second travel-related cognitive persona corresponding to a second archetype user model, the second travel-related cognitive persona comprising a second sub-graph within the cognitive graph, the second sub-graph including a second set of nodes and second weighted edges between the second set of nodes in the cognitive graph;

receiving an inquiry, including contextual data for the user;

based on the contextual data for the user, selecting the first travel-related cognitive persona or the second travel-related cognitive persona;

generating a plurality of ranked travel-related cognitive insights for the user based on the selected travel-related cognitive persona by:

following the edges of the cognitive graph to determine a third set of nodes of the cognitive graph, each of the third set of nodes associated with one of the plurality of ranked travel related cognitive insights based on the set of nodes and weighted edges of the selected travel-related cognitive persona and the cognitive graph; and

returning the ranked travel-related cognitive insights in response to the inquiry.

2. The system of claim 1 , wherein:

the first travel-related cognitive persona represents a set of attributes, each of the set of attributes corresponding to a node of the first set of nodes; and

an amount of weighting between nodes of the first set of nodes corresponds to a degree of relevance between the first travel-related cognitive persona and the attributes.

3. The system of claim 2 , wherein the set of attributes comprises at least one of demographic attributes, geographic attributes, psychographic attributes, and behavioristic attributes.

4. The system of claim 1 , wherein the instructions are

further for:

receiving feedback from the user relating to the selected travel-related cognitive persona; and

revising weighting of the links among the set of nodes of the cognitive graph using the feedback.

5. The system of claim 4 , wherein the instructions are further for using the revised weighting to generate a third travel-related cognitive persona.

6. The system of claim 1 , wherein the first set of nodes of the first travel-related cognitive persona and the second set of nodes of the second travel-related cognitive persona include at least some of the same nodes.

7. The non-transitory computer readable medium of claim 6 , further comprising instructions for using the revised weighting to generate a third travel-related cognitive persona.

8. A method comprising;

receiving streams of data from a plurality of data sources;

incorporating the data into a cognitive graph comprising a set of nodes and edges by incorporating one or more entities determined from data into the cognitive graph by incorporating one or more sub-graphs into the cognitive graph so that the cognitive graph includes at least one node representing those one or more entitles and one or more links between the at least one node representing those one or more entitles and one or more of the other set of nodes of the cognitive graph;

defining a first travel-related cognitive persona within the cognitive graph, the first travel-related cognitive persona corresponding to a first archetype user model, the first travel-related cognitive persona comprising a first sub-graph within the cognitive graph, the first sub-graph including a first set of nodes and first weighted edges between the first set of nodes in the cognitive graph;

defining a second travel-related cognitive persona within the cognitive graph, the second travel-related cognitive persona corresponding to a second archetype user model, the second travel-related cognitive persona comprising a second sub-graph within the cognitive graph, the second sub-graph including a second set of nodes and second weighted edges between the second set of nodes in the cognitive graph;

receiving an inquiry, including contextual data for the user;

based on the contextual data for the user, selecting the first travel-related cognitive persona or the second travel-related cognitive persona;

generating a plurality of ranked travel-related cognitive insights for the user based on the selected travel-related cognitive persona by:

following the edges of the cognitive graph to determine a third set of nodes of the cognitive graph, each of the third set of nodes associated with one of the plurality of ranked travel related cognitive insights based on the set of nodes and weighted edges of the selected travel-related cognitive persona and the cognitive graph; and

returning the ranked travel-related cognitive insights in response to the inquiry.

9. The method of claim 8 , wherein:

the first travel-related cognitive persona represents a set of attributes, each of the set of attributes corresponding to a node of the first set of nodes; and

an amount of weighting between nodes of the first set of nodes corresponds to a degree of relevance between the first travel-related cognitive persona and the attributes.

10. The method of claim 9 , wherein:

the set of attributes comprise at least one of demographic attributes, geographic attributes, psychographic attributes, and behavioristic attributes.

11. The method of claim 8 , further comprising:

receiving feedback from the user relating to the selected travel-related cognitive persona; and

revising weighting of the links among the set of nodes of the cognitive graph using the feedback.

12. The method of claim 11 , further comprising using the revised weighting to generate a third travel-related cognitive persona.

13. The method of claim 8 , wherein the first set of nodes of the first travel-related cognitive persona and the second set of nodes of the second travel-related cognitive persona include at least some of the same nodes.

14. A non-transitory computer readable medium,

comprising instructions for:

receiving streams of data from a plurality of data sources;

incorporating the data into a cognitive graph comprising a set of nodes and edges by incorporating one or more entities determined from data into the cognitive graph by incorporating one or more sub-graphs into the cognitive graph so that the cognitive graph includes at least one node representing those one or more entitles and one or more links between the at least one node representing those one or more entitles and one or more of the other set of nodes of the cognitive graph;

defining a first travel-related cognitive persona within the cognitive graph, the first travel-related cognitive persona corresponding to a first archetype user model, the first travel-related cognitive persona comprising a first sub-graph within the cognitive graph, the first sub-graph including a first set of nodes and first weighted edges between the first set of nodes in the cognitive graph;

defining a second travel-related cognitive persona within the cognitive graph, the second travel-related cognitive persona corresponding to a second archetype user model, the second travel-related cognitive persona comprising a second sub-graph within the cognitive graph, the second sub-graph including a second set of nodes and second weighted edges between the second set of nodes in the cognitive graph;

receiving an inquiry, including contextual data for the user;

based on the contextual data for the user; selecting the first travel-related cognitive persona or the second travel-related cognitive persona;

generating a plurality of ranked travel-related cognitive insights for the user based on the selected travel-related cognitive persona by:

following the edges of the cognitive graph to determine a third set of nodes of the cognitive graph, each of the third set of nodes associated with one of the plurality of ranked travel related cognitive insights based on the set of nodes and weighted edges of the selected travel-related cognitive persona and the cognitive graph; and

returning the ranked travel-related cognitive insights in response to the inquiry.

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

the first travel-related cognitive persona represents a set of attributes, each of the set of attributes corresponding to a node of the first set of nodes; and

an amount of weighting between nodes of the first set of nodes corresponds to a degree of relevance between the first travel-related cognitive persona and the attributes.

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

the set of attributes comprise at least one of demographic attributes, geographic attributes, psychographic attributes, and behavioristic attributes.

17. The non-transitory computer readable medium of claim 15 , wherein the first set of nodes of the first travel-related cognitive persona and the second set of nodes of the second travel-related cognitive persona include at least some of the same nodes.

18. The non-transitory computer readable medium of claim 14 , further comprising instructions for:

receiving feedback from the user relating to the selected travel-related cognitive persona; and

revising weighting of the links among the set of nodes of the cognitive graph using the feedback.