Universal Quantification of Knowledge Elements Within a Cognitive Graph

• US 20170329869A1
• Filed: 10/11/2016
• Published: 11/16/2017
• Est. Priority Date: 05/13/2016
• Status: Active Grant

• Current Assignee: Tecnotree Technologies Incorporated
• Original Assignee: Cognitive Scale Inc (Tecnotree Oyj)
• Inventors: Lindsley, Hannah R.
• Granted Patent: US 10,860,936 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 16/84 Mapping; Conversion
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/90335 Query processing
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/043 Distributed expert systems; Blackboards
• CPC Class Codes: G06N 5/048 Fuzzy inferencing

Abstract

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 data from a plurality of data sources; processing the data from the plurality of data sources, the processing the data from the plurality of data sources identifying a plurality of knowledge elements; and, storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data, each knowledge element being structurally defined within the cognitive graph.

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 and configured for;

receiving data from a plurality of data sources;

processing the data from the plurality of data sources, the processing the data from the plurality of data sources identifying a plurality of knowledge elements; and

,

storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data, each knowledge element being structurally defined within the cognitive graph.

2. The system of claim 1, wherein:

structurally defining a knowledge element comprises storing a knowledge element within the cognitive graph based upon a set of categories of the knowledge element and a set of attributes of the knowledge element.

3. The system of claim 2, wherein:

a relationship between a first knowledge element and a second knowledge element comprises only one of a categorical relationship and an attributive relationship.

4. The system of claim 1, wherein:

the collection of knowledge elements are accurately and precisely modeled via at least one of a ladder entailment pattern and a diamond entailment pattern.

5. The system of claim 1, wherein:

inheritance relationships between a base node and a parent node define a particular concept within the cognitive graph.

6. The system of claim 1, wherein:

a plurality of knowledge elements representing quantity concepts are stored within the cognitive graph, the plurality of knowledge elements representing quantity concepts enabling quantity to be modeled within the cognitive graph.

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

receiving data from a plurality of data sources;

processing the data from the plurality of data sources, the processing the data from the plurality of data sources identifying a plurality of knowledge elements; and

,

storing the knowledge elements within the cognitive graph as a collection of knowledge elements, the storing universally representing knowledge obtained from the data, each knowledge element being structurally defined within the cognitive graph.

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

structurally defining a knowledge element comprises storing a knowledge element within the cognitive graph based upon a set of categories of the knowledge element and a set of attributes of the knowledge element.

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

a relationship between a first knowledge element and a second knowledge element comprises only one of a categorical relationship and an attributive relationship.

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

the collection of knowledge elements are accurately and precisely modeled via at least one of a ladder entailment pattern and a diamond entailment pattern.

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

inheritance relationships between a base node and a parent node define a particular concept within the cognitive graph.

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

a plurality knowledge elements representing quantity concepts are stored within the cognitive graph, the plurality of knowledge elements representing quantity concepts enabling quantity to be modeled within the cognitive graph.

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.