System for refining cognitive insights using travel-related cognitive graph vectors

• US 9,898,552 B2
• Filed: 06/08/2015
• Issued: 02/20/2018
• Est. Priority Date: 06/09/2014
• Status: Active Grant

• Current Assignee: RealPage Incorporated
• Original Assignee: WayBlazer, Inc
• Inventors: Kothe, Kyle W., Goldberg, Scott E., Faith, John N.
• Primary Examiner(s): Woo, Isaac M
• Application Number:
  US14/733,248
• Publication Number:
  US 20150356201A1
• Time in Patent Office: 988 Days
• Field of Search: 707600-899
• CPC Class Codes: G06F 16/2237 Vectors, bitmaps or matrices
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence

Abstract

A method, system and computer-usable medium are disclosed for using travel-related cognitive graph vectors.

Claims

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 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.

2. 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 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, the first travel-related cognitive graph vector comprising a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus;

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, the second travel-related cognitive graph vector comprising a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;

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, wherein 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.

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 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 5, 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 program code, the computer program code comprising computer executable instructions configured 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;

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.

8. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured 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, the first travel-related cognitive graph vector comprising a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus;

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, the second travel-related cognitive graph vector comprising a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;

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, wherein 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.

9. The non-transitory, computer-readable storage medium of claim 8, 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.

10. The non-transitory, computer-readable storage medium of claim 9, 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 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.

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 are substantially similar magnitudes.

13. The non-transitory, computer-readable storage medium of claim 8, 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 8, wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.

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, the first travel-related cognitive graph vector comprising a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus;

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, the second travel-related cognitive graph vector comprising a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus;

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, wherein 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.

16. The method of claim 15, 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.

17. The method of claim 16, 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 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.

18. The method of claim 17, wherein:

at least some of the first cognitive graph vector indices, second cognitive graph vector indices and third vector graph indices are different magnitudes.

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 substantially similar magnitudes.