Thomas C Lehman

US Patent:

8619955, Dec 31, 2013

Filed:

Nov 22, 2011

Appl. No.:

13/302154

Inventors:

Balaji Gopalakrishnan - Cary NC, US
William Elliot Inman - Cary NC, US
Thomas Robert Lehman - Holly Springs NC, US
John Clare Brocklebank - Raleigh NC, US

Assignee:

SAS Institute Inc. - Cary NC

International Classification:

H04M 15/00
G06Q 30/00

US Classification:

379133, 37911201, 705 1443, 705 1457, 705 1472

Abstract:

In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated. A probability density function may be generated from the call distribution and used in the generation of the advertisement distribution plan.

US Patent:

20130159348, Jun 20, 2013

Filed:

Dec 16, 2011

Appl. No.:

13/327949

Inventors:

Bruce Monroe Mills - Cary NC, US
John Courtney Haws - Durham NC, US
John Clare Brocklebank - Raleigh NC, US
Thomas Robert Lehman - Holly Springs NC, US

International Classification:

G06F 17/30

US Classification:

707777, 707E17005, 707E17014

Abstract:

Systems and methods are provided for generating a set of classifiers. A location is determined for each instance of a topic term in a collection of documents. One or more topic term phrases are identified, and one or more sentiment terms within each topic term phrase. Candidate classifiers are identified by parsing words in the one or more topic term phrases, and a colocation matrix is generated. A seed row of the colocation associated with a particular attribute is identified, and distance metrics are determined by comparing each row of the colocation matrix to the seed row. A set of classifiers are generated for the particular attribute, where classifiers in the set of classifiers are selected using the distance metrics.

US Patent:

20130325437, Dec 5, 2013

Filed:

May 30, 2012

Appl. No.:

13/483504

Inventors:

Thomas Lehman - Holly Springs NC, US
Jody Porowski - Raleigh NC, US
Bruce Monroe Mills - Cary NC, US
Michael T. Brooks - Raleigh NC, US
Heather Michelle Goodykoontz - Raleigh NC, US

International Classification:

G06F 17/27

US Classification:

704 9

Abstract:

Computer-implemented systems and methods are provided for determining an overall mood score of a document. For example, the document is received from a computer-readable medium. A text segment in a document is identified to be indicative of a mood of the document. The text segment is mapped to a mood scale among a predetermined set of mood scales. A mood weight associated with the mood scale for the text segment is generated. An overall mood score of the document is determined based at least in part on the mood weight.

US Patent:

20150317390, Nov 5, 2015

Filed:

Jul 13, 2015

Appl. No.:

14/798320

Inventors:

- Cary NC, US
John Courtney Haws - Durham NC, US
John Clare Brocklebank - Raleigh NC, US
Thomas Robert Lehman - Holly Springs NC, US

International Classification:

G06F 17/30

Abstract:

Systems and methods are provided for generating a set of classifiers. A term is identified within a document and a pre-defined threshold distance is determined. A plurality of additional terms in the document are identified, the additional terms being located within the pre-defined threshold distance of the time. A distance between the term and an additional term of the plurality of additional terms is calculated. A corresponding weight for the calculated distance is determined using a proximity weighting scheme. A score for the additional term is calculated using the calculated distance and the corresponding weight. A colocation matrix is generated and a classifier determined using the colocation matrix.

US Patent:

20140156382, Jun 5, 2014

Filed:

Nov 25, 2013

Appl. No.:

14/089235

Inventors:

- Cary NC, US
William Elliot Inman - Cary NC, US
Thomas Robert Lehman - Holly Springs NC, US
John Clare Brocklebank - Raleigh NC, US

Assignee:

SAS Institute Inc. - Cary NC

International Classification:

G06Q 30/02

US Classification:

705 1443

Abstract:

In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated. A probability density function may be generated from the call distribution, where the probability density function is for determining a probability that a telephone call will be received by the business entity in response to advertisement information delivered to a call location, and wherein the probability density function expresses the probability as a function of distance between the call location and the business entity. The probability density function may then be used in the generation of the advertisement distribution plan.