IP Library Granted Patent US 11,494,360
Granted Patent B2
US 11,494,360 · App. 16/895,004 · Granted Nov 8, 2022

Adaptive correlation of user-specific compressed multidimensional data profiles to engagement rules

Inventors: Vijay Perincherry (Potomac, MD); Janine Gelbart (Bethesda, MD); Marc Inzelstein (North Bethesda, MD)
Assignee: INDIGGO LLC
G06F16/2264G06F16/907G06N5/022G06N20/00
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 11,494,360
App. No.
16/895,004
Granted
Nov 8, 2022
Kind
B2
Abstract

Some embodiments relate generally to the processing of compressed multidimensional data and selection of engagement rules based on the compressed multidimensional data. In some embodiments, a method includes retrieving, via a processor, a multidimensional data profile that includes a set of first inclination distributions, each associated with a data dimension. The processor matches a first set of engagement rules to the multidimensional data profile to define a matched set, each engagement rule of the first set of engagement rules having a corresponding confidence level and a corresponding set of second inclination distributions. The processor selects an engagement rule from the matched set that has a corresponding confidence level no less than a corresponding confidence level for each remaining engagement rule from the matched set, and sends a signal causing display of a stimulus to a user according to the selected engagement rule and not according to the remaining engagement rules.

Claims (398)

1. A method, comprising:

matching, via a processor, a first plurality of engagement rules to a compressed multidimensional data profile, to define a matched plurality of engagement rules, the matching performed according to:

ID

(

X

,

I

)

(

m

)

ID

(

X

,

R

)

=

(

Σ

(

min

(

lean

(

X

,

I

)

i

,

lean

(

X

,

R

)

i

)

)

,

i

=

1

,

10

(

min

(

inc

(

X

,

I

)

,

inc

(

X

,

R

)

)

)

)

(

Σ

(

lean

(

X

,

I

)

i

)

,

i

=

1

,

10

(

min

(

inc

(

X

,

I

)

,

inc

(

X

,

R

)

)

)

)

,

where (m) is a matching operator, X is a data dimension of a plurality of data dimensions of the compressed multidimensional data profile, ID(X,I) is an inclination distribution of a first plurality of inclination distributions of the compressed multidimensional data profile, ID(X,R) is an inclination distribution of a second plurality of inclination distributions of the compressed multidimensional data profile, inc(X, I) is a time increment of the inclination distribution of the first plurality of inclination distributions, inc(X, R) is a time increment of the inclination distribution of the second plurality of inclination distributions, lean(X, I) is a value of the inclination distribution of the first plurality of inclination distributions, and lean(X, R) is a value of the inclination distribution of the second plurality of inclination distributions;

sending, via the processor, a signal causing display, via a user interface operably coupled to the processor, of a stimulus to a user based on an engagement rule from the matched plurality of engagement rules;

receiving, at the processor and in response to an interaction of the user with the user interface, a representation of a response to the stimulus;

defining an effectiveness of at least one engagement rule from the matched plurality of engagement rules based on the response; and

automatically modifying, via the processor, a confidence level of the at least one engagement rule from the matched plurality of engagement rules, based on the effectiveness, to define a second plurality of engagement rules different from the first plurality of engagement rules.

2. The method of claim 1 , further comprising iteratively modifying the compressed multidimensional data profile based on a response to the stimulus.

3. The method of claim 1 , further comprising iteratively modifying the first plurality of engagement rules based on a response to the stimulus.

4. The method of claim 1 , wherein at least one inclination distribution from the first plurality of inclination distributions is a multimodal distribution.

5. The method of claim 1 , wherein at least one inclination distribution from the second plurality of inclination distributions is a multimodal distribution.

6. An apparatus, comprising:

a memory;

a processor operably coupled to the memory; and

a user interface operably coupled to at least one of the memory or the processor,

the processor configured to:

match a first set of engagement rules to a compressed multidimensional data profile stored in the memory, to produce a matched set of engagement rules, the matching performed according to:

ID

(

X

,

I

)

(

m

)

ID

(

X

,

R

)

=

(

Σ

(

min

(

lean

(

X

,

I

)

i

,

lean

(

X

,

R

)

i

)

)

,

i

=

1

,

10

(

min

(

inc

(

X

,

I

)

,

inc

(

X

,

R

)

)

)

)

(

Σ

(

lean

(

X

,

I

)

i

)

,

i

=

1

,

10

(

min

(

inc

(

X

,

I

)

,

inc

(

X

,

R

)

)

)

)

,

where (m) is a matching operator, X is a data dimension of a plurality of data dimensions of the compressed multidimensional data profile, ID(X,I) is an inclination distribution of a first plurality of inclination distributions of the compressed multidimensional data profile, ID(X,R) is an inclination distribution of a second plurality of inclination distributions of the compressed multidimensional data profile, inc(X, I) is a time increment of the inclination distribution of the first plurality of inclination distributions, inc(X, R) is a time increment of the inclination distribution of the second plurality of inclination distributions, lean(X, I) is a value of the inclination distribution of the first plurality of inclination distributions, and lean(X, R) is a value of the inclination distribution of the second plurality of inclination distributions;

send a signal to cause display, via the user interface, of a stimulus to a user based on an engagement rule from the matched set of engagement rules;

receive, in response to an interaction of the user with the user interface, a representation of a response to the stimulus;

define an effectiveness of at least one engagement rule from the matched plurality of engagement rules based on the response; and

automatically modify a confidence level of the at least one engagement rule from the matched set of engagement rules, based on the effectiveness, to define a second set of engagement rules different from the first set of engagement rules.

7. The apparatus of claim 6 , wherein the processor is further configured to:

store, in the memory, a plurality of confidence levels, each confidence level from the plurality of confidence levels corresponding to an engagement rule of the set of engagement rules; and

modify at least one confidence level from the plurality of confidence levels based on an input received via the user interface in response to the displayed stimulus.

8. The apparatus of claim 6 , wherein:

each inclination distribution from the first plurality of inclination distributions corresponds to a data dimension from the plurality of data dimensions, and

each inclination distribution from the second plurality of inclination distributions corresponds to a data dimension from the plurality of data dimensions.

9. The apparatus of claim 6 , wherein the processor is further configured to iteratively modify the compressed multidimensional data profile based on an input received via the user interface in response to the displayed stimulus.

10. The apparatus of claim 6 , wherein the processor is further configured to iteratively modify the set of engagement rules in response to the displayed stimulus.

11. The apparatus of claim 6 , wherein the processor is further configured to match the set of engagement rules to the compressed multidimensional data profile based on an aggregation of overlaps between: (1) inclination distributions of the first plurality of inclination distributions; and (2) inclination distributions of the second plurality of inclination distributions.

12. An apparatus, comprising:

a memory; and

a processor operably coupled to the memory and configured to:

match a compressed multidimensional data profile stored in the memory to a first set of engagement rules to produce a matched set of engagement rules, the processor configured to match according to:

ID

(

X

,

I

)

(

m

)

ID

(

X

,

R

)

=

(

Σ

(

min

(

lean

(

X

,

I

)

i

,

lean

(

X

,

R

)

i

)

)

,

i

=

1

,

10

(

min

(

inc

(

X

,

I

)

,

inc

(

X

,

R

)

)

)

)

(

Σ

(

lean

(

X

,

I

)

i

)

,

i

=

1

,

10

(

min

(

inc

(

X

,

I

)

,

inc

(

X

,

R

)

)

)

)

,

where (m) is a matching operator, X is a data dimension of a plurality of data dimensions of the compressed multidimensional data profile, ID(X,I) is an inclination distribution of the first plurality of inclination distributions, ID(X,R) is an inclination distribution of the second plurality of inclination distributions, inc(X, I) is a time increment of the inclination distribution of the first plurality of inclination distributions, inc(X, R) is a time increment of the inclination distribution of the second plurality of inclination distributions, lean(X, I) is a value of the inclination distribution of the first plurality of inclination distributions, and lean(X, R) is a value of the inclination distribution of the second plurality of inclination distributions;

send a signal to cause display, via a user interface, of a stimulus to a user based on an engagement rule from the matched set of engagement rules;

receive, in response to an interaction of the user with the user interface, a representation of a response to the stimulus;

define an effectiveness of at least one engagement rule from the matched set of engagement rules based on the response; and

automatically modify a confidence level of the at least one engagement rule from the matched set of engagement rules, based on the effectiveness, to define a second set of engagement rules different from the first set of engagement rules.

13. The apparatus of claim 12 , wherein the processor is further configured to iteratively modify the compressed multidimensional data profile based on a response to the stimulus, the response received via the user interface.

14. The apparatus of claim 12 , wherein the processor is further configured to iteratively modify the set of engagement rules based on a response to the stimulus.

15. The apparatus of claim 12 , wherein at least one inclination distribution of the first plurality of inclination distributions is a multimodal distribution.

16. The apparatus of claim 12 , wherein at least one inclination distribution of the second plurality of inclination distributions is a multimodal distribution.

Assignments (2)
CHANGE OF NAME Recorded Nov 3, 2021
From: INDIGGO ASSOCIATES, LLC
To: INDIGGO LLC
Reel/Frame 058790/0639 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 8, 2020
From: PERINCHERRY, VIJAY; GELBART, JANINE; INZELSTEIN, MARC
To: INDIGGO ASSOCIATES LLC
Reel/Frame 052862/0801 →
Continuity (3)
Continuation 16458801 · Jul 1, 2019
Continuation 15092351 · Apr 6, 2016
Related Publication 20200302341A1 · Sep 24, 2020