Method for refining cognitive insights using cognitive graph vectors

• US 9,514,418 B2
• Filed: 02/24/2015
• Issued: 12/06/2016
• Est. Priority Date: 06/09/2014
• Status: Active Grant

• Current Assignee: Tecnotree Technologies Incorporated
• Original Assignee: Cognitive Scale Inc (Tecnotree Oyj)
• Inventors: Sanchez, Matthew
• Primary Examiner(s): Hill, Stanley K
• Assistant Examiner(s): BROWN JR, NATHAN H
• Application Number:
  US14/629,740
• Publication Number:
  US 20160171389A1
• Time in Patent Office: 651 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

A method, system and computer-usable medium for using cognitive graph vectors to refine cognitive insights.

Claims

1. A method for refining cognitive insights using cognitive graph vectors comprising:

storing data from a plurality of data sources within a cognitive graph, the plurality of data sources comprising at least one of a social data source stored in a social data repository, public data source stored in a public data repository, licensed data source stored in a licensed data repository and proprietary data source stored in a proprietary data repository;

associating a first set of the data within the cognitive graph with a first cognitive graph vector of a plurality of cognitive graph vectors;

associating a second set of the data within the cognitive graph with a second cognitive graph vector of the plurality of cognitive graph vectors;

processing the data from the plurality of data sources to provide cognitive insights; and

refining the cognitive insights based upon a limitation relating to one of the plurality of cognitive graph vectors; and

,

providing the cognitive insights to a destination via a cognitive insight stream, the cognitive insight stream comprising a stream of visualized insights, the destination comprising a cognitive application, the cognitive application enabling a user to interact with the cognitive insights.

2. The method of claim 1, wherein:

the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus;

the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph vector;

the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices; and

the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices.

3. The method of claim 1, further comprising:

associating a third set of data within the cognitive graph with a third cognitive graph vector of the plurality of cognitive graph vectors; and

, wherein

the refining the cognitive insights based upon the limitation relating to one of the plurality of cognitive graph vectors further comprises identifying a limitation on one of the first, second and third cognitive graph vectors and refining another of the first, second and third cognitive graph vectors based upon the limitation of one of the first, second and third cognitive graph vectors.

4. The method of claim 3, wherein:

the first cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first cognitive graph vector away from a cognitive graph nexus;

the second cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second cognitive graph vector away from the cognitive graph vector;

the third cognitive graph vector comprises a plurality of third cognitive graph vector indices extending along the third cognitive graph vector away from the cognitive graph vector;

the limitation comprises limiting the first set of data to data within a first certain index of the plurality of first cognitive graph vector indices;

the refining comprising limiting the second set of data to data within a second certain index of the second cognitive graph vector indices and data within a third; and

the refining further comprising limiting the third set of data to data within a third certain index of the third cognitive graph vector indices.

5. The method 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 method 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 substantially similar magnitudes.