IP Library › Granted Patent US 11,288,317

Granted Patent B2

US 11,288,317 · App. 16/740,057 · Granted Mar 29, 2022

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

Inventors: Kyle W. Kothe (Austin, TX); Scott E. Goldberg (Park City, UT); John N. Faith (Austin, TX)

Assignee: REALPAGE, INC.

G06F16/9024 G06F16/2237

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Quick Facts

Patent No.: US 11,288,317
App. No.: 16/740,057
Granted: Mar 29, 2022
Kind: B2

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USPTO Patent Center↗ Full Patent PDF↗

Abstract

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

Claims (58)

1. A system comprising:

a processor; and

a non-transitory computer readable medium embodying computer instructions for providing cognitive insights using cognitive graph vectors and executable by the processor for:

storing data from a plurality of data sources within a cognitive graph,

wherein the cognitive graph depicts relationships between people, places, and things over time; and

wherein the stored data includes learned knowledge from past observations and feedback;

associating a first set of the 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 data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and

evaluating the data from the plurality of data sources to provide a travel-related cognitive insight based upon a limitation relating to one of the plurality of travel-related cognitive graph vectors and the first set of data or the second set of data.

2. A system comprising:

a processor; and

a non-transitory computer readable medium embodying computer instructions for providing cognitive insights using cognitive graph vectors and executable by the processor for:

storing data from a plurality of data sources within a cognitive graph;

associating a first set of the 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 data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and

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; and

wherein 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.

3. The system of claim 2 , wherein the instructions are further for refining the travel-related cognitive insight based upon the limitation relating to one of the plurality of travel-related cognitive graph vectors.

4. The system of claim 3 , wherein the data is within a first certain index of the plurality of first cognitive graph vector indices and within a second certain index of the second cognitive graph vector indices.

5. The system of claim 2 , wherein the first travel-related cognitive graph vector and the second travel-related cognitive graph vector are each associated with travel related attributes.

6. The system of claim 5 , wherein the first travel-related cognitive graph vector and the second travel-related cognitive graph vector are one of who, where, how, when, what, or why.

7. A method, comprising:

storing data from a plurality of data sources within a cognitive graph,

wherein the cognitive graph depicts relationships between people, places, and things over time; and

wherein the stored data includes learned knowledge from past observations and feedback;

associating a first set of the 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 data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and

8. A method, comprising:

storing data from a plurality of data sources within a cognitive graph;

associating a first set of the 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 data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and

9. The method of claim 8 , further comprising refining the travel-related cognitive insight based upon the limitation relating to one of the plurality of travel-related cognitive graph vectors.

10. The method of claim 9 , wherein the data is within a first certain index of the plurality of first cognitive graph vector indices and within a second certain index of the second cognitive graph vector indices.

11. The method of claim 8 , wherein the first travel-related cognitive graph vector and the second travel-related cognitive graph vector are each associated with travel related attributes.

12. The method of claim 11 , wherein the first travel-related cognitive graph vector and the second travel-related cognitive graph vector are one of who, where, how, when, what, or why.

13. A non-transitory computer readable medium, comprising instructions for:

storing data from a plurality of data sources within a cognitive graph,

wherein the cognitive graph depicts relationships between people, places, and things over time; and

wherein the stored data includes learned knowledge from past observations and feedback;

associating a first set of the 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 data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and

14. A non-transitory computer readable medium, comprising instructions for:

storing data from a plurality of data sources within a cognitive graph;

associating a first set of the 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 data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of travel-related cognitive graph vectors; and

15. The non-transitory computer readable medium of claim 14 , further comprising instructions for refining the travel-related cognitive insight based upon the limitation relating to one of the plurality of travel-related cognitive graph vectors.

16. The non-transitory computer readable medium of claim 15 , wherein the data is within a first certain index of the plurality of first cognitive graph vector indices and within a second certain index of the second cognitive graph vector indices.

17. The non-transitory computer readable medium of claim 14 , wherein the first travel-related cognitive graph vector and the second travel-related cognitive graph vector are each associated with travel related attributes.

18. The non-transitory computer readable medium of claim 17 , wherein the first travel-related cognitive graph vector and the second travel-related cognitive graph vector are one of who, where, how, when, what, or why.

Assignments (5)

RELEASE OF SECOND LIEN SECURITY INTEREST IN PATENTS AT R/F 056256/0184 Recorded Dec 18, 2024

From: GOLDMAN SACHS BANK USA, AS COLLATERAL AGENT

To: REALPAGE, INC.

Reel/Frame 069717/0388 →

ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 20, 2021

From: KOTHE, KYLE W.; GOLDBERG, SCOTT E.; FAITH, JOHN N.

To: WAYBLAZER, INC.

Reel/Frame 057846/0431 →

SECOND LIEN PATENT SECURITY AGREEMENT Recorded May 17, 2021

From: REALPAGE, INC.

To: GOLDMAN SACHS BANK USA, AS COLLATERAL AGENT