Travel-related cognitive profiles

• US 10,521,475 B2
• Filed: 06/05/2015
• Issued: 12/31/2019
• Est. Priority Date: 06/09/2014
• Status: Active Grant

• Current Assignee: RealPage Incorporated
• Original Assignee: RealPage Incorporated
• Inventors: Faith, John N., Kothe, Kyle W.
• Primary Examiner(s): Waldron, Scott A.
• Assistant Examiner(s): Figueroa, Kevin W
• Application Number:
  US14/731,846
• Publication Number:
  US 20150356416A1
• Time in Patent Office: 1,670 Days
• CPC Class Codes: G06F 13/4208 being a system bus, e.g. VME bus, Futurebus, Multibus
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/287 Visualization; Browsing
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06F 16/972 Access to data in other repository systems, e.g. legacy data or dynamic Web page generation
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: H04W 4/025 using location based information parameters

Abstract

A method, system and computer-usable medium for performing cognitive computing operations comprising receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph; defining a travel-related cognitive persona within the cognitive graph, the travel-related cognitive persona corresponding to an archetype user model, the travel-related cognitive persona comprising a set of nodes in the cognitive graph; associating a user with the travel-related cognitive persona; defining a travel-related cognitive profile within the cognitive graph, the travel-related cognitive profile comprising an instance of the travel-related cognitive persona that references personal data associated with the user; associating the user with the travel-related cognitive profile; and, performing a cognitive computing operation based upon the travel-related cognitive profile associated with the user.

Claims

1. A system comprising:

a processor;

a data bus coupled to the processor; and

a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor for;

receiving streams of data from a plurality of data sources;

processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph comprising a set of nodes and edges by;

processing the streams of data from the plurality of data sources to perform entity detection on the streams of data from the plurality of data sources, and

incorporating the enriched data into the cognitive graph by incorporating one or more entities determined from the entity detection into the cognitive graph by;

generating one or more sub-graphs comprising at least one node representing the one or more entities determined from the entity detection, and

incorporating the 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 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 including a second set of nodes and second weighted edges between the second set of nodes in the cognitive graph;

defining a travel-related cognitive profile within the cognitive graph, the travel-related cognitive profile comprising a third sub-graph within the cognitive graph including a third set of nodes corresponding to personal data of a user, wherein the third set of nodes is associated with the first set of nodes of the first sub-graph comprising the first travel-related cognitive persona and the second set of nodes of the second sub-graph comprising the second travel-related cognitive persona with third weighted edges;

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 fourth set of nodes of the cognitive graph, each of the fourth 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, the third set of nodes of the travel-related cognitive profile and the third weighted edges associating the selected travel-related cognitive persona with the travel-related cognitive profile; and

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

2. The system of claim 1, wherein:

the personal data comprises data associated with an interaction of the user with the cognitive graph.

3. The system of claim 1, wherein:

the personal data is distributed among the plurality of data sources.

4. The system of claim 3, wherein the instructions executable by the processor further comprise instructions for:

aggregating the personal data distributed among the plurality of data sources to define the travel-related cognitive profile.

5. The system of claim 1, wherein:

the travel-related cognitive profile represents a plurality of attributes associated with the user; and

each of the plurality of attributes corresponds to a node within the set of nodes in the cognitive graph.

6. The system of claim 1, wherein the instructions executable by the processor further comprise instructions for:

receiving user provided personal information; and

,

associating the user with the travel-related cognitive profile based upon user provided personal information.

7. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions for:

receiving streams of data from a plurality of data sources;

processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching for incorporation into a cognitive graph comprising a set of nodes and edges by;

processing the streams of data from the plurality of data sources to perform entity detection on the streams of data from the plurality of data sources, and

incorporating the enriched data into the cognitive graph by incorporating one or more entities determined from the entity detection into the cognitive graph by;

generating one or more sub-graphs comprising at least one node representing the one or more entities determined from the entity detection, and

incorporating the 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 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 including a second set of nodes and second weighted edges between the second set of nodes in the cognitive graph;

defining a travel-related cognitive profile within the cognitive graph, the travel-related cognitive profile comprising a third sub-graph within the cognitive graph including a third set of nodes corresponding to personal data of a user, wherein the third set of nodes is associated with the first set of nodes of the first sub-graph comprising the first travel-related cognitive persona and the second set of nodes of the second sub-graph comprising the second travel-related cognitive persona with third weighted edges;

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 fourth set of nodes of the cognitive graph, each of the fourth 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, the third set of nodes of the travel-related cognitive profile and the third weighted edges associating the selected travel-related cognitive persona with the travel-related cognitive profile; and

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

8. The non-transitory, computer-readable storage medium of claim 7, wherein:

the personal data comprises data associated with an interaction of the user with the cognitive graph.

9. The non-transitory, computer-readable storage medium of claim 7, wherein:

the personal data is distributed among the plurality of data sources.

10. The non-transitory, computer-readable storage medium of claim 9, wherein the instructions executable by the processor further comprise instructions for:

aggregating the personal data distributed among the plurality of data sources to define the travel-related cognitive profile.

11. The non-transitory, computer-readable storage medium of claim 7, wherein:

the travel-related cognitive profile represents a plurality of attributes associated with the user; and

each of the plurality of attributes corresponds to a node within the set of nodes in the cognitive graph.

12. The non-transitory, computer-readable storage medium of claim 7, wherein the instructions executable by the processor further comprise instructions for:

using the feedback from the user to create a new travel-related cognitive persona, the new persona inheriting a common set of attributes from the travel-related cognitive persona.

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.