John C Torres

US Patent:

20210158381, May 27, 2021

Filed:

Dec 7, 2020

Appl. No.:

17/114041

Inventors:

- New York NY, US
Michael Sheppard - Brooklyn NY, US
Peter Lipa - Tucson AZ, US
Alejandro Terrazas - Santa Cruz CA, US
John Charles Torres - San Diego CA, US

International Classification:

G06Q 30/02
G06N 5/04
G06N 20/00
G06N 3/08

Abstract:

Methods and apparatus to facilitate dynamic classification for market research are disclosed. Example disclosed methods include constructing, using a programmed processor based on data for a sample population and a first set of input variables, a self-organizing map classifying the sample population according to a plurality of classes defined in the map using fuzzy class membership. Example disclosed methods include extracting the fuzzy class membership for the sample population from the map. Example disclosed methods include correlating fuzzy class membership with behavior data for the sample population to determine a likely class behavior for the plurality of classes. Example disclosed methods include using fuzzy class membership and the likely class behavior to provide a predictive market output in response to a query.

US Patent:

20170148042, May 25, 2017

Filed:

Nov 25, 2015

Appl. No.:

14/951944

Inventors:

- New York NY, US
Michael Sheppard - Brooklyn NY, US
Peter Lipa - Tucson AZ, US
Alejandro Terrazas - Santa Cruz CA, US
John Charles Torres - San Diego CA, US

International Classification:

G06Q 30/02
G06N 99/00
G06N 5/04

Abstract:

Methods and apparatus to facilitate dynamic classification for market research are disclosed. Example disclosed methods include constructing, using a programmed processor based on data for a sample population and a first set of input variables, a self-organizing map classifying the sample population according to a plurality of classes defined in the map using fuzzy class membership. Example disclosed methods include extracting the fuzzy class membership for the sample population from the map. Example disclosed methods include correlating fuzzy class membership with behavior data for the sample population to determine a likely class behavior for the plurality of classes. Example disclosed methods include using fuzzy class membership and the likely class behavior to provide a predictive market output in response to a query.