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Sterling M Smith, 59Huntersville, NC

Known as:
Sterling Michael Smith Sterling Pamela Smith Michael Sterling Smith Sterlins M Smith Michael S Smith Merrill Smith Sterling
Related to:
Krista Leigh Everett 42

Sterling Smith Phones & Addresses

Huntersville, NC   

12159 Dearview Ln, Charlotte, NC 28269    704-9489203   

814 Stargard Ct, Charlotte, NC 28270    704-7084143   

Houston, TX   

2415 San Ramon Valley Blvd #42, San Ramon, CA 94583   

2415 San Ramon Valley Blvd STE 4, San Ramon, CA 94583   

2473 Camino De Jugar, San Ramon, CA 94583    925-8311265   

Colorado Springs, CO   

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Mentions for Sterling M Smith

Career records & work history

Lawyers & Attorneys

Sterling Smith Photo 1

Sterling Smith - Lawyer

Specialties:
Administrative and Public, Oil & Gas
ISLN:
903593425
Admitted:
1978
University:
Washington & Lee University, B.A., 1975
Law School:
University of Texas School of Law, J.D., 1978
Sterling Smith Photo 2

Sterling Smith - Lawyer

Specialties:
Civil Trial, Real Estate, Taxation, Litigation, Public Law
ISLN:
903593432
Admitted:
1978
University:
California State University at Sacramento, B.A., 1974
Law School:
McGeorge School of Law, University of the Pacific, J.D., 1978

License Records

Sterling Randall Smith

Licenses:
License #: 23014 - Active
Category: Architect
Issued Date: Mar 1, 2012
Expiration Date: Apr 30, 2017
Organization:
Firm Not Published

Publications & IP owners

Us Patents

Check Image Distribution And Processing System And Method

US Patent:
5784610, Jul 21, 1998
Filed:
Nov 21, 1994
Appl. No.:
8/342978
Inventors:
John Ray Copeland - Decatur AL
Leslie Marie Doby - Matthews NC
Larry Page Hobbs - Charlotte NC
Vil Patrick Johnikin - Charlotte NC
Julie Ann Pridmore - Charlotte NC
Sterling Richardson Smith - Charlotte NC
Thomas Chester Smith - Charlotte NC
Lori London Weaver - Salisbury NC
Filip Jay Yeskel - Charlotte NC
Assignee:
International Business Machines Corporation - Armon NY
International Classification:
G06F 1500
G06F 1730
US Classification:
395615
Abstract:
A digital document image archive and distribution system includes an archive system and a distributed digital document image retrieval system. The system has communication nodes located at an image capture site and at one or more remote archive retrieval sites, these sites forming a communications network operating as a chained client/server network composed of workstation components and a capture site host computer component. An originating remote workstation retrieves a digital document image from the image capture site by creating a transaction file that identifies a digital document image to be retrieved. This transaction file is sent to a remote server workstation whereat a plurality of transaction files are batched by priority. The batched transaction files are transmitted to the capture site workstation whereat the host component retrieves a group of digital document images from archive storage, including the digital document image that is identified by the transaction file. The host then sends the group of digital document images to a capture site server workstation, which workstation then sends the group of digital document images from the capture site server workstation to the remote server workstation, whereupon the group of digital document images is sent from the remote server workstation to the originating remote workstation.

Selective Deep Parsing Of Natural Language Content

US Patent:
2022033, Oct 20, 2022
Filed:
Jun 28, 2022
Appl. No.:
17/851584
Inventors:
- Armonk NY, US
David B. Werts - Charlotte NC, US
Sterling R. Smith - Apex NC, US
International Classification:
G06F 40/205
G06F 40/14
Abstract:
Mechanisms are provided to perform selective deep parsing of natural language content. A targeted deep parse natural language processing system is configured to recognize one or more triggers that specify elements within natural language content that indicate a portion of natural language content that is to be targeted with a deep parse operation. A portion of natural language content is received and a pre-deep parse scan operation is performed on the natural language content based on the one or more triggers to identify one or more sub-portions of the natural language content that contain at least one of the one or more triggers. A deep parse is performed on only the one or more sub-portions of the portion of natural language content that contain at least one of the one or more triggers, while other sub-portions of the portion of natural language content are not deep parsed.

Selective Deep Parsing Of Natural Language Content

US Patent:
2021034, Nov 4, 2021
Filed:
Jul 14, 2021
Appl. No.:
17/375106
Inventors:
- Armonk NY, US
David B. Werts - Charlotte NC, US
Sterling R. Smith - Raleigh NC, US
International Classification:
G06F 40/205
G06F 40/14
Abstract:
Mechanisms are provided to perform selective deep parsing of natural language content. A targeted deep parse natural language processing system is configured to recognize one or more triggers that specify elements within natural language content that indicate a portion of natural language content that is to be targeted with a deep parse operation. A portion of natural language content is received and a pre-deep parse scan operation is performed on the natural language content based on the one or more triggers to identify one or more sub-portions of the natural language content that contain at least one of the one or more triggers. A deep parse is performed on only the one or more sub-portions of the portion of natural language content that contain at least one of the one or more triggers, while other sub-portions of the portion of natural language content are not deep parsed.

Selective Deep Parsing Of Natural Language Content

US Patent:
2021008, Mar 25, 2021
Filed:
Sep 20, 2019
Appl. No.:
16/576906
Inventors:
- Armonk NY, US
David B. Werts - Charlotte NC, US
Sterling R. Smith - Apex NC, US
International Classification:
G06F 17/22
G06F 17/27
G06F 17/24
G06N 5/04
G06F 16/332
Abstract:
Mechanisms are provided to perform selective deep parsing of natural language content. A targeted deep parse natural language processing system is configured to recognize one or more triggers that specify elements within natural language content that indicate a portion of natural language content that is to be targeted with a deep parse operation. A portion of natural language content is received and a pre-deep parse scan operation is performed on the natural language content based on the one or more triggers to identify one or more sub-portions of the natural language content that contain at least one of the one or more triggers. A deep parse is performed on only the one or more sub-portions of the portion of natural language content that contain at least one of the one or more triggers, while other sub-portions of the portion of natural language content are not deep parsed.

Possible Relatives

Cynthia Smith  David Y Smith  A Smith  Cyril E Smith  Cyrus R Smith  D J Smith  Davida W Smith  Sterling Johnson  Sterling S Standage  Sterling C Jones 

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