Cognitive attribution

• US 10,643,139 B2
• Filed: 09/25/2017
• Issued: 05/05/2020
• Est. Priority Date: 04/20/2017
• Status: Active Grant

• Current Assignee: Tecnotree Technologies Incorporated
• Original Assignee: Cognitive Scale Inc (Tecnotree Oyj)
• Inventors: Chawla, Neeraj, Sanchez, Matthew, Ricaurte, Andrea M., Ranatunga, Dilum, Acharya, Ayan, Lindsley, Hannah R.
• Primary Examiner(s): Hsieh, Ping
• Application Number:
  US15/714,325
• Publication Number:
  US 20180307990A1
• Time in Patent Office: 953 Days
• CPC Class Codes: G06F 16/243 Natural language query formulation
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/5854 using shape and object relationship
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing
• CPC Class Codes: G06F 16/957 Browsing optimisation, e.g. caching or content distillation
• 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: G06N 5/041 Abduction
• CPC Class Codes: G06N 5/043 Distributed expert systems; Blackboards
• CPC Class Codes: G06T 7/11 Region-based segmentation

Abstract

A method, system and computer readable medium for generating a cognitive insight comprising: receiving content element data, the content element data representing a content element, the content element comprising an element of a corpus of content; performing a cognitive learning operation on the content element data, the cognitive learning operation identifying descriptive information associated with the content element; associating a cognitive attribute with the content element using the descriptive information associated with the content element.

Claims

1. A computer-implementable method for performing a cognitive attribution operation comprising:

receiving content element data, the content element data representing a content element, the content element comprising an element of a corpus of content;

performing a cognitive learning operation on the content element data, the cognitive learning operation identifying descriptive information associated with the content element, the cognitive learning operation generating a hierarchical abstraction of topics from the descriptive information associated with the content element, the cognitive learning operation being performed by a cognitive inference and learning system, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive engine, the cognitive engine comprising a dataset engine, a graph query engine and an insight/learning engine, the dataset engine being implemented to establish and maintain a dynamic data ingestion and enrichment pipeline, the graph query engine being implemented to receive and process queries such that the queries are bridged into a cognitive graph, the insight/learning engine being implemented to generate a cognitive insight from the cognitive graph, the dataset engine, the graph query engine and the insight/learning engine operating collaboratively to generate the cognitive insight;

associating a cognitive attribute with the content element using the descriptive information associated with the content element; and

,

generating the cognitive insight using the attribute associated with the content element.

2. The method of claim 1, wherein:

the content element data comprises an image data element; and

,

the cognitive learning operation comprising performing a computer vision operation on the content element data.

3. The method of claim 2, wherein:

the computer vision operation segments portions of the image data element to provide a segmented image comprising a plurality of image segments; and

,

the plurality of image segments are processed to determine respective cognitive attributes.

4. The method of claim 3, wherein:

the respective cognitive attributes are associated with at least one cognitive attribute class; and

,

an image segment of the plurality of image segments is associated with a corresponding cognitive attribute class.

5. The method of claim 2, wherein:

the content element comprises descriptive information related to the image data element; and

,

the cognitive learning operation comprises performing a natural language processing operation on the descriptive information related to the image data element to generate a cognitive attribute associated with the description information.

6. The method of claim 5, wherein:

the cognitive attribute associated with the descriptive information is associated with at least one cognitive attribute class.

7. 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 and configured for;

receiving content element data, the content element data representing a content element, the content element comprising an element of a corpus of content;

performing a cognitive learning operation on the content element data, the cognitive learning operation generating a hierarchical abstraction of topics from the descriptive information associated with the content element the cognitive learning operation identifying descriptive information associated with the content element, the cognitive learning operation being performed by a cognitive inference and learning system, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive engine, the cognitive engine comprising a dataset engine, a graph query engine and an insight/learning engine, the dataset engine being implemented to establish and maintain a dynamic data ingestion and enrichment pipeline, the graph query engine being implemented to receive and process queries such that the queries are bridged into a cognitive graph, the insight/learning engine being implemented to generate a cognitive insight from the cognitive graph, the dataset engine, the graph query engine and the insight/learning engine operating collaboratively to generate the cognitive insight;

associating a cognitive attribute with the content element using the descriptive information associated with the content element; and

,

generating the cognitive insight using the attribute associated with the content element.

8. The system of claim 7, wherein:

the content element data comprises an image data element; and

,

the cognitive learning operation comprising performing a computer vision operation on the content element data.

9. The system of claim 8, wherein:

the computer vision operation segments portions of the image data element to provide a segmented image comprising a plurality of image segments; and

,

the plurality of image segments are processed to determine respective cognitive attributes.

10. The system of claim 9, wherein:

the respective cognitive attributes are associated with at least one cognitive attribute class; and

,

an image segment of the plurality of image segments is associated with a corresponding cognitive attribute class.

11. The system of claim 8, wherein:

the content element comprises descriptive information related to the image data element; and

,

the cognitive learning operation comprises performing a natural language processing operation on the descriptive information related to the image data element to generate a cognitive attribute associated with the description information.

12. The system of claim 11, wherein:

the cognitive attribute associated with the descriptive information is associated with at least one cognitive attribute class.

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

receiving content element data, the content element data representing a content element, the content element comprising an element of a corpus of content;

performing a cognitive learning operation on the content element data, the cognitive learning operation generating a hierarchical abstraction of topics from the descriptive information associated with the content element the cognitive learning operation identifying descriptive information associated with the content element, the cognitive learning operation being performed by a cognitive inference and learning system, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform comprising

a cognitive engine, the cognitive engine comprising a dataset engine, a graph query engine and an insight/learning engine, the dataset engine being implemented to establish and maintain a dynamic data ingestion and enrichment pipeline, the graph query engine being implemented to receive and process queries such that the queries are bridged into a cognitive graph, the insight/learning engine being implemented to generate a cognitive insight from the cognitive graph, the dataset engine, the graph query engine and the insight/learning engine operating collaboratively to generate the cognitive insight;

associating a cognitive attribute with the content element using the descriptive information associated with the content element and,

generating the cognitive insight using the attribute associated with the content element.

14. The non-transitory, computer-readable storage medium of claim 13, wherein:

the content element data comprises an image data element; and

,

the cognitive learning operation comprising performing a computer vision operation on the content element data.

15. The non-transitory, computer-readable storage medium of claim 14, wherein:

the computer vision operation segments portions of the image data element to provide a segmented image comprising a plurality of image segments; and

,

the plurality of image segments are processed to determine respective cognitive attributes.

16. The non-transitory, computer-readable storage medium of claim 15, wherein:

the respective cognitive attributes are associated with at least one cognitive attribute class; and

,

an image segment of the plurality of image segments is associated with a corresponding cognitive attribute class.

17. The non-transitory, computer-readable storage medium of claim 14, wherein:

the content element comprises descriptive information related to the image data element; and

,

the cognitive learning operation comprises performing a natural language processing operation on the descriptive information related to the image data element to generate a cognitive attribute associated with the description information.

18. The non-transitory, computer-readable storage medium of claim 17, wherein:

the cognitive attribute associated with the descriptive information is associated with at least one cognitive attribute class.

19. The non-transitory, computer-readable storage medium of claim 13, wherein the computer executable instructions are deployable to a client system from a server system at a remote location.

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