IP Library Granted Patent US 11,893,512
Granted Patent B2
US 11,893,512 · App. 14/983,023 · Granted Feb 6, 2024

Method for generating an anonymous cognitive profile

Inventors: Neeraj Chawla (Austin, TX); Joshua L. Segars (Cedar Park, TX); Matthew Sanchez (Austin, TX)
Assignee: Tecnotree Technologies, Inc.
G06N5/043G06F16/00G06F16/337
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Quick Facts
Patent No.
US 11,893,512
App. No.
14/983,023
Granted
Feb 6, 2024
Kind
B2
Abstract

A cognitive learning method comprising: monitoring a user interaction of an anonymous user; generating user interaction data based upon the user interaction; receiving data from a plurality of data sources; processing the user interaction data and the data from the plurality of data sources to perform a cognitive learning operation, the processing being performed via a cognitive inference and learning system, the cognitive learning operation comprising analyzing the user interaction data, the cognitive learning operation generating a cognitive learning result based upon the user interaction data; and, associating an anonymous cognitive profile with the anonymous user based the cognitive learning result.

Claims (23)

1. A cognitive learning method comprising:

monitoring a user interaction of an anonymous user;

generating user interaction data based upon the user interaction;

receiving data from a plurality of data sources;

processing the user interaction data and the data from the plurality of data sources to perform a cognitive learning operation, the processing being performed via a cognitive inference and learning system executing on an information processing system, the cognitive learning operation comprising analyzing the user interaction data, the cognitive learning operation generating a cognitive learning result based upon the user interaction data, the cognitive learning operation implementing a cognitive learning technique according to a cognitive learning framework, the cognitive learning framework comprising a plurality of cognitive learning styles and a plurality of cognitive learning categories, each of the plurality of cognitive learning styles comprising a generalized learning approach implemented by the cognitive inference and learning system to perform the cognitive learning operation, each of the plurality of cognitive learning categories referring to a source of information used by the cognitive inference and learning system when performing the cognitive learning operation, an individual cognitive learning technique being associated with a primary cognitive learning style and bounded by an associated primary cognitive learning category, the learning operation applying the cognitive learning technique via a machine learning algorithm to generate the cognitive learning result, the cognitive inference and learning system comprising a cognitive platform, the cognitive platform and the information processing system performing a cognitive computing function, the cognitive platform comprising:

a cognitive graph, the cognitive graph being derived from the plurality of data sources, the cognitive graph comprising an application cognitive graph, the application cognitive graph comprising a cognitive graph associated with a cognitive application, interactions between the cognitive application and the application cognitive graph being represented as a set of nodes in the cognitive graph, and,

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 an anonymous cognitive profile with the anonymous user based on the cognitive learning result, the anonymous cognitive profile comprising a cognitive profile associated with a particular anonymous user; and,

generating the cognitive insight based upon specific attributes of the cognitive profile associated with the particular anonymous user; and wherein

the plurality of cognitive learning techniques comprising a direct correlations cognitive learning technique, an explicit likes/dislikes cognitive learning technique, a patterns and concepts cognitive learning technique, a behavior cognitive learning technique, a concept entailment cognitive learning technique, and a contextual recommendation cognitive learning technique, the direct correlations cognitive learning technique being associated with a declared learning style and bounded by a data-based cognitive learning category, the explicit likes/dislikes cognitive technique being associated with the declared learning style and bounded by an interaction-based cognitive learning category, the patterns and concepts cognitive learning technique being associated with an observed learning style and bounded by the data-based cognitive learning category, the behavior cognitive learning technique being associated with the observed learning style and bounded by the interaction-based cognitive learning category, the concept entailment cognitive learning technique being associated with an inferred learning style and bounded by the data-based cognitive learning category, and the contextual recommendation cognitive technique being associated with the inferred learning style and bounded by the interaction-based cognitive learning category.

2. The cognitive learning method of claim 1 , wherein:

the user interaction interacts with a plurality of cognitive suggestions; and,

the interaction data comprises at least one of an order of an interaction, an amount of time of an interaction, and a particular area within the plurality of cognitive suggestions the user interacted with for at least one of the plurality of cognitive suggestions.

3. The cognitive learning method of claim 1 , wherein:

receipt of the data from the plurality of sources is monitored to provide data related user interaction data; and,

the data related user interaction data is used to generate the cognitive insight.

4. The cognitive learning method of claim 3 , further comprising:

receiving feedback from the anonymous user regarding the cognitive insight; and,

updating the cognitive learning result based upon the feedback.

5. The cognitive learning method of claim 4 , wherein:

the feedback comprises at least one of selecting the cognitive insight for receipt of additional information, not selecting the cognitive insight, and submitting a new query in response to receipt of the cognitive insight.

6. The cognitive learning method of claim 4 , wherein:

the interaction data and the feedback is used to refine the anonymous cognitive profile associated with the anonymous user.

Assignments (5)
SECURITY INTEREST Recorded Dec 22, 2022
From: TECNOTREE TECHNOLOGIES INC.
To: TRIPLEPOINT CAPITAL LLC
Reel/Frame 062213/0388 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 14, 2022
From: COGNITIVE SCALE, INC.; COGNITIVESCALE SOFTWARE INDIA PVT. LTD.; COGNITIVE SCALE UK LTD.; COGNITIVE SCALE (CANADA) INC.
To: TECNOTREE TECHNOLOGIES, INC.
Reel/Frame 062125/0051 →
SECURITY INTEREST Recorded Oct 25, 2022
From: COGNITIVE SCALE INC.
To: TRIPLEPOINT CAPITAL LLC
Reel/Frame 061771/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 19, 2020
From: SANCHEZ, MATTHEW
To: COGNITIVE SCALE, INC.
Reel/Frame 052985/0388 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 8, 2017
From: CHAWLA, NEERAJ; SEGARS, JOSHUA L.
To: COGNITIVE SCALE, INC.
Reel/Frame 041502/0986 →
Continuity (1)
Related Publication 20170185918A1 · Jun 29, 2017