System for refining cognitive insights using travel-related cognitive graph vectors
A method, system and computer-usable medium are disclosed for using travel-related cognitive graph vectors.
1. A system comprising:
a processor; and
a non-transitory computer readable medium embodying computer instructions for refining cognitive insights using cognitive graph vectors and executable by the processor for:
storing travel-related data from a plurality of data sources within a cognitive graph;
associating a first set of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors;
associating a second set of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors;
evaluating the travel-related data from the plurality of data sources to provide a travel-related cognitive insight; and
refining the travel-related cognitive insight based upon a limitation relating to one of the plurality of travel-related cognitive graph vectors.
2. A system comprising:
a processor; and
a non-transitory computer readable medium embodying computer instructions for refining cognitive insights using cognitive graph vectors and executable by the processor for:
storing travel-related data from a plurality of data sources within a cognitive graph;
associating a first set of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors;
associating a second set of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors;
evaluating the travel-related data from the Plurality of data sources to provide a travel-related cognitive insight; and
refining the travel-related cognitive insight based upon a limitation relating to one of the plurality of travel-related cognitive graph vectors, wherein
the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus;
the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices; and
the refining comprising limiting the second set of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices.
3. The system of claim 2 , further comprising:
associating a third set of travel-related data within the cognitive graph with a third travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and, wherein the refining of the travel-related cognitive insights based upon the limitation relating to one of the plurality of travel-related cognitive graph vectors further comprises identifying a limitation on one of the first, second and third travel-related cognitive graph vectors and refining another of the first, second and third travel-related cognitive graph vectors based upon the limitation of one of the first, second and third cognitive travel-related graph vectors.
4. The system of claim 3 , wherein:
the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus;
the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;
the third travel-related cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third travel-related cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices;
the refining comprising limiting the second set of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices and travel-related data within a third set of travel-related data; and
the refining further comprising limiting the third set of travel-related data to travel-related data within a third certain index of the third cognitive graph vector indices.
5. The system of claim 4 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are different magnitudes.
6. The system of claim 4 wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are substantially similar magnitudes.
7. A non-transitory, computer-readable storage medium embodying computer executable instructions for:
storing travel-related data from a plurality of data sources within a cognitive graph;
associating a first set of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors;
associating a second set of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors;
evaluating the travel-related data from the plurality of data sources to provide a travel-related cognitive insights; and
refining the travel-related cognitive insight based upon a limitation relating to one of the plurality of travel-related cognitive graph vectors.
8. The non-transitory, computer-readable storage medium of claim 7 , further comprising:
associating a third set of travel-related data within the cognitive graph with a third travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and, wherein
the refining of the travel-related cognitive insights based upon the limitation relating to one of the plurality of travel-related cognitive graph vectors further comprises identifying a limitation on one of the first, second and third travel-related cognitive graph vectors and refining another of the first, second and third travel-related cognitive graph vectors based upon the limitation of one of the first, second and third travel-related cognitive graph vectors.
9. The non-transitory, computer-readable storage medium of claim 8 , wherein:
the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus;
the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;
the third travel-related cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third travel-related cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices;
the refining comprising limiting the second set of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices and data within a third set or travel-related data; and
the refining further comprising limiting the third set of travel-related data to travel-related data within a third certain index of the third cognitive graph vector indices.
10. The non-transitory, computer-readable storage medium of claim 9 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are different magnitudes.
11. The non-transitory, computer-readable storage medium of claim 9 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are substantially similar magnitudes.
12. The non-transitory, computer-readable storage medium of claim 7 , wherein the computer executable instructions are deployable to a client system from a server system at a remote location.
13. The non-transitory, computer-readable storage medium of claim 7 , wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.
14. A non-transitory, computer-readable storage medium embodying computer executable instructions for:
storing travel-related data from a plurality of data sources within a cognitive graph;
associating a first set of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors;
associating a second set of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors;
evaluating the travel-related data from the plurality of data sources to provide a travel-related cognitive insight; and
refining the travel-related cognitive insight based upon a limitation relating to one of the plurality of travel-related cognitive graph vectors, wherein:
the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus;
the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices; and
the refining comprising limiting the second set of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices.
15. A method comprising:
storing travel-related data from a plurality of data sources within a cognitive graph;
associating a first set of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors;
associating a second set of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors;
processing the travel-related data from the plurality of data sources to provide travel-related cognitive insights; and
refining the travel-related cognitive insights based upon a limitation relating to one of the plurality of travel-related cognitive graph vectors.
16. The method of claim 15 , wherein:
the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus;
the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices; and
the refining comprises limiting the second set of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices.
17. The method of claim 16 , further comprising:
associating a third set of travel-related data within the cognitive graph with a third travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and, wherein
the refining of the travel-related cognitive insights based upon the limitation relating to one of the plurality of travel-related cognitive graph vectors further comprises identifying a limitation on one of the first, second and third travel-related cognitive graph vectors and refining another of the first, second and third travel-related cognitive graph vectors based upon the limitation of one of the first, second and third cognitive travel-related graph vectors.
18. The method of claim 17 , wherein:
the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus;
the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;
the third travel-related cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third travel-related cognitive graph vector away from the cognitive graph nexus;
the refining comprising limiting the second set of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices and travel-related data within a third set of travel-related data; and
the refining further comprising limiting the third set of travel-related data to travel-related data within a third certain index of the third cognitive graph vector indices.
19. The method of claim 18 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are different magnitudes.
20. The method of claim 18 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are substantially similar magnitudes.