Daniel W Lambert

US Patent:

20200013079, Jan 9, 2020

Filed:

Sep 16, 2019

Appl. No.:

16/571630

Inventors:

- Armonk NY, US
Daniel T. Lambert - Manhattan NY, US

International Classification:

G06Q 30/02
G06N 20/00
G06F 16/28
G06F 16/955
G06F 16/9535
G06Q 10/06
G06Q 50/00

Abstract:

Embodiments herein provide data clustering and user modeling for next-best-action decisions. Specifically, a modeling tool is configured to: receive indicators within unstructured social data from a plurality of users; analyze the unstructured social data of each of the plurality of users to assign a set of feature vectors to each of the plurality of users, each feature vector corresponding to one or more personality characteristics of each of the plurality of users; and analyze the feature vectors to identify two or more users from the plurality of users sharing a set of similar feature vectors. The modeling tool is further configured to: group the two or more users from the plurality of users sharing the set of similar feature vectors to form a cluster; identify attributes of the cluster; and input the attributes of the cluster into a predictive model to determine an offer corresponding to the cluster.

US Patent:

20160042372, Feb 11, 2016

Filed:

Oct 22, 2015

Appl. No.:

14/919852

Inventors:

- Armonk NY, US
Daniel T. Lambert - Manhattan NY, US

International Classification:

G06Q 30/02
G06N 99/00
G06Q 10/06
G06F 17/30
G06Q 50/00

Abstract:

Embodiments herein provide data clustering and user modeling for next-best-action decisions. Specifically, a modeling tool is configured to: receive indicators within unstructured social data from a plurality of users; analyze the unstructured social data of each of the plurality of users to assign a set of feature vectors to each of the plurality of users, each feature vector corresponding to one or more personality characteristics of each of the plurality of users; and analyze the feature vectors to identify two or more users from the plurality of users sharing a set of similar feature vectors. The modeling tool is further configured to: group the two or more users from the plurality of users sharing the set of similar feature vectors to form a cluster; identify attributes of the cluster; and input the attributes of the cluster into a predictive model to determine an offer corresponding to the cluster.