IP Library Granted Patent US 11,748,646
Granted Patent B2
US 11,748,646 · App. 15/705,820 · Granted Sep 5, 2023

Database query and data mining in intelligent distributed communication networks

Inventors: Thomas Mathew (Vienna, VA); John William Seaman (Reston, VA); Jorge Luis Vasquez (Fairfax, VA); Reza Ali Manouchehri (Reston, VA); Lee Evan Kohn (Arlington, VA)
Assignee: Zoomph, Inc.
G06N7/01G06N5/02G06Q10/101G06Q30/00G06Q30/02G06Q50/01
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,748,646
App. No.
15/705,820
Granted
Sep 5, 2023
Kind
B2
Abstract

A system includes a processor and a memory device communicatively coupled to the processor. The system also includes a database communicatively coupled to the processor. The database is configured to store a first plurality of prediction sets. Each prediction set is associated with a respective individual within a first population. Each prediction set comprises a plurality of prediction results, and each prediction result corresponds to a selected one of a plurality of features. The processor is configured to receive a request for a distribution value associated with a selected feature and one or more parameters. The distribution value indicate how often the selected feature appears in a second population of individuals, the second population being defined by the one or more parameters.

Claims (26)

1. A server comprising:

a processor;

a memory device communicatively coupled to the processor; and

wherein the processor is configured to obtain a first plurality of prediction sets by determining a plurality of probability distributions associated with a characteristic of an individual and use a probabilistic classifier to generate a merged probability distribution based on the plurality of probability distributions;

a database communicatively coupled to the processor, configured to store the first plurality of prediction sets, each prediction set being associated with a respective characteristic of an individual within a first population, each prediction set comprising a plurality of prediction results, each prediction result corresponding to a selected one of a plurality of features associated with the characteristic; and

wherein the processor is configured to

generate a plurality of distribution values associated with the selected one feature by determining, for each respective prediction result, a respective distribution value for the selected one feature based on the respective plurality of corresponding prediction results in a respective prediction result group;

determine an average distribution value based on the plurality of distribution values, the average distribution value indicating how often the selected feature appears as a characteristic in a second population of individuals;

select an advertisement image based on the average distribution value; and

display the advertisement image on a first display in a particular location among a plurality of displays in various locations, wherein the first display is selected for the advertisement image based on a percentage distribution of a prediction result associated with the selected one of the plurality of features, among the plurality of prediction results, predicted to be present among the characteristics of the individuals in the particular location.

2. The server of claim 1 , wherein the processor is further configured to filter the first plurality of prediction sets based on the one or more parameters, generating a second plurality of prediction sets.

3. The server of claim 2 , wherein the processor is further configured to define a plurality of prediction result groups, each prediction result group comprising a plurality of corresponding prediction results selected from the second plurality of prediction sets, wherein each plurality of corresponding prediction results includes one prediction result selected from each of the second plurality of prediction sets.

4. The server of claim 1 , wherein the processor is further configured to provide the average distribution value to a display device, wherein the display device is configured to display the distribution value using an interactive graphical user interface (GUI).

5. A method comprising:

obtaining, a first plurality of prediction sets by determining a plurality of probability distributions associated with a characteristic of an individual and use a probabilistic classifier to generate a merged probability distribution based on the plurality of probability distributions;

storing the first plurality of prediction sets, each prediction set being associated with a respective characteristic of an individual within a first population, each prediction set comprising a plurality of prediction results, each prediction result corresponding to a selected one of a plurality of features associated with the characteristic;

generating a plurality of distribution values associated with the selected one feature by determining, for each respective prediction result, a respective distribution value for the selected one feature based on the respective plurality of corresponding prediction results in a respective prediction result group;

determining an average distribution value based on the plurality of distribution values, the average distribution value indicating how often the selected feature appears as a characteristic in a second population of individuals;

selecting; an advertisement image based on the average distribution value; and

displaying the advertisement image on a first display in a particular location among a plurality of displays in various locations, wherein the first display is selected for the advertisement image based on a percentage distribution of a prediction result associated with the selected one of the plurality of features, among the plurality of prediction results, predicted to be present among the characteristics of the individuals in the particular location.

6. The method of claim 5 , further comprising:

filtering the first plurality of prediction sets based on the one or more parameters, generating a second plurality of prediction sets.

7. The method of claim 6 , further comprising:

defining a plurality of prediction result groups, each prediction result group comprising a plurality of corresponding prediction results selected from the second plurality of prediction sets.

8. The method of claim 7 , wherein each plurality of corresponding prediction results includes one prediction result selected from each of the second plurality of prediction sets.

9. The method of claim 5 , wherein the display device is configured to display the distribution value using an interactive graphical user interface (GUI).

Assignments (2)
SECURITY INTEREST Recorded Jan 2, 2025
From: ZOOMPH, INC.
To: AVIDBANK
Reel/Frame 069726/0020 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 30, 2017
From: MATHEW, THOMAS; KOHN, LEE EVAN; SEAMAN, JOHN WILLIAM; MANOUCHEHRI, ALI REZA; VASQUEZ, JORGE LUIS
To: ZOOMPH, INC.
Reel/Frame 043748/0238 →
Continuity (4)
Continuation In Part 15594526 · May 12, 2017
Continuation 15347777 · Nov 9, 2016
Continuation 14968596 · Dec 14, 2015
Related Publication 20180129962A1 · May 10, 2018