System for refining cognitive insights using cognitive graph vectors
A system and computer-usable medium for using cognitive graph vectors to refine cognitive insights.
1. A system comprising:
a processor;
a data bus coupled to the processor; and
a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code used for refining cognitive insights using cognitive graph vectors and comprising instructions executable by the processor and configured for:
storing data from a plurality of data sources within a cognitive graph, the cognitive graph representing a data domain;
associating a first set of the data of the data domain within the cognitive graph with a first cognitive graph vector of a plurality of cognitive graph vectors, the first cognitive graph vector extending away from a cognitive graph nexus in a first direction;
associating a second set of the data within the cognitive graph with a second cognitive graph vector of the plurality of cognitive graph vectors, the second cognitive graph vector extending away from the cognitive graph nexus in a second direction;
processing the data from the plurality of data sources to provide cognitive insights; and
refining the cognitive insights based upon a limitation relating to one of the plurality of cognitive graph vectors, the limitation corresponding to a selected cognitive graph vector parameter.
2. The system of claim 1 , wherein:
the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from the cognitive graph nexus;
the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices; and
the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices.
3. The system of claim 1 , further comprising:
associating a third set of data within the cognitive graph with a third cognitive graph vector of the plurality of cognitive graph vectors; and, wherein
the refining the cognitive insights based upon the limitation relating to one of the plurality of cognitive graph vectors further comprises identifying a limitation on one of the first, second and third cognitive graph vectors and refining another of the first, second and third cognitive graph vectors based upon the limitation of one of the first, second and third cognitive graph vectors.
4. The system of claim 3 , wherein:
the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from the cognitive graph nexus;
the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph nexus;
the third cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices;
the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices and data within a third; and
the refining further comprising limiting the third set of data to 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 5 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices have a corresponding magnitude.
7. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:
storing data from a plurality of data sources within a cognitive graph, the cognitive graph representing a data domain;
associating a first set of the data of the data domain within the cognitive graph with a first cognitive graph vector of a plurality of cognitive graph vectors, the first cognitive graph vector extending away from a cognitive graph nexus in a first direction;
associating a second set of the data within the cognitive graph with a second cognitive graph vector of the plurality of cognitive graph vectors, the second cognitive graph vector extending away from the cognitive graph nexus in a second direction;
processing the data from the plurality of data sources to provide cognitive insights; and
refining the cognitive insights based upon a limitation relating to one of the plurality of cognitive graph vectors, the limitation corresponding to a selected cognitive graph vector parameter.
8. The non-transitory, computer-readable storage medium of claim 7 , wherein:
the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from the cognitive graph nexus;
the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices; and
the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices.
9. The non-transitory, computer-readable storage medium of claim 7 , further comprising:
associating a third set of data within the cognitive graph with a third cognitive graph vector of the plurality of cognitive graph vectors; and, wherein
the refining the cognitive insights based upon the limitation relating to one of the plurality of cognitive graph vectors further comprises identifying a limitation on one of the first, second and third cognitive graph vectors and refining another of the first, second and third cognitive graph vectors based upon the limitation of one of the first, second and third cognitive graph vectors.
10. The non-transitory, computer-readable storage medium of claim 9 , wherein:
the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from the cognitive graph nexus;
the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph nexus;
the third cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third cognitive graph vector away from the cognitive graph nexus;
the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices;
the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices and data within a third; and
the refining further comprising limiting the third set of data to data within a third certain index of the third cognitive graph vector indices.
11. The non-transitory, computer-readable storage medium of claim 10 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are different magnitudes.
12. The non-transitory, computer-readable storage medium of claim 11 , wherein:
at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices have a corresponding magnitude.
13. 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.
14. 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.