Paul G Florack

US Patent:

20200177729, Jun 4, 2020

Filed:

Feb 3, 2020

Appl. No.:

16/780580

Inventors:

- Reston VA, US
Ken Cartwright - Berryville VA, US
Amit Singla - Seattle WA, US
Srikanth Mohan - Reston VA, US
Paul Florack - Leawood KS, US

Assignee:

Transaction Network Services, Inc. - Reston VA

International Classification:

H04M 3/436
H04Q 11/06
H04Q 3/00
G06N 20/00
H04M 3/42

Abstract:

Systems and methods are disclosed for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.

US Patent:

20190230223, Jul 25, 2019

Filed:

Mar 29, 2019

Appl. No.:

16/369282

Inventors:

- Reston VA, US
Ken Cartwright - Berryville VA, US
Amit Singla - Seattle WA, US
Srikanth Mohan - Reston VA, US
Paul Florack - Leawood KS, US

Assignee:

Transaction Network Services, Inc. - Reston VA

International Classification:

H04M 3/436
H04Q 3/00
G06N 20/00

Abstract:

Systems and methods are disclosed for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.

US Patent:

20180324297, Nov 8, 2018

Filed:

Nov 1, 2017

Appl. No.:

15/801019

Inventors:

- Reston VA, US
Ken Cartwright - Berryville VA, US
Amit Singla - Seattle WA, US
Srikanth Mohan - Reston VA, US
Paul Florack - Leawood KS, US

Assignee:

Transaction Network Services, Inc. - Reston VA

International Classification:

H04M 3/436
H04Q 3/00
H04M 3/42
G06N 99/00

Abstract:

Systems and methods are disclosed for using machine-learning techniques for labeling incoming calls with categories relating to a risk level. A model is generated using call log data. The call log data is augmented using information from additional data sources to generate features for the model. The model may then be used to categorize additional incoming calls. The model may be used in real-time to categorize incoming calls, or categorization results may be stored for a plurality of calling numbers. Various embodiments provide various technical advantages by virtue of how the components of the system are deployed between an endpoint communication device, a telephony provider system, and possibly other systems.