Scott M Sims

US Patent:

20190378050, Dec 12, 2019

Filed:

Jun 12, 2018

Appl. No.:

16/006470

Inventors:

- Charlotte NC, US
Craig Douglas Widmann - Chandler AZ, US
Scott A. Sims - Tega Cay SC, US
Margaret A. Payne - Elkton MD, US
Ronnie J. Morris - Mesquite TX, US
Joel Filliben - Newark DE, US
Eren Kursun - New York NY, US

International Classification:

G06N 99/00
G06F 17/30
G06Q 30/00

Abstract:

Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. An ensemble machine learning system is coupled to a graph module storing a graph structure, wherein a collection of entities and the relationships between those entities forms nodes and connection arcs between the various nodes. A hotfile module and hotfile propagation engine coordinate with the graph module or may be subsumed within the graph module, and implement the various hot file functionality generated by the machine learning systems.

US Patent:

20190289025, Sep 19, 2019

Filed:

Mar 14, 2018

Appl. No.:

15/921395

Inventors:

- Charlotte NC, US
Craig D. Widmann - Chandler AZ, US
Dharmender Kumar Satija - Rye Brook NY, US
Andrew DongHo Kim - Glendale AZ, US
Shawn Parris Bench - Wilmington DE, US
Kolt Arthur Bell - Charlotte NC, US
Scott Anderson Sims - Tega Cay SC, US

International Classification:

H04L 29/06
H04L 12/26
G06F 17/30
G06N 99/00

Abstract:

The invention describes a system and method employing machine learning and artificial intelligence engines to monitor data streams in real-time across multiple channels in order to detect anomalies and generate prioritized alerts. In particular, the invention may continuously collect data across multiple channels. The obtained data may be compared with reference data to continuously update a confidence level associated with the user, channel, entity, or other identifying factor. Based on the confidence level, profile the user to detect any inconsistencies in the data collected over time and generate an alert to the user in question and potentially to other downstream users or entities. In this way, the invention not only provides a way to detect anomalies in a cross-channel fashion, but also creates a mechanism for feedback wherein the system may incorporate user feedback to resolve alerts and detected anomalies.