IP Library Patent Application 15993557
Patent Application
App. No. 15/993,557

DIGITAL CREDENTIAL RECEIVER PERFORMANCE MODEL

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Quick Facts
Patent No.
US None
App. No.
15/993,557
Abstract

Techniques described herein relate to determining model profiles of credential receivers corresponding to particular field objects. A digital credential platform server may receive data corresponding to a plurality of credential receivers, identify particular subsets of the credential receivers associated with particular field data objects, and then determine and analyze credential receiver data to determine sets of capabilities associated with the receiver. The determined sets of capabilities associated with each credential receiver may be analyzed, and based on the analyses, one or more model profiles of capabilities may be generated for the field data object. The various analyses may include regression analyses, trained machine learning algorithms, and/or other mathematical analyses capable of identifying model capabilities profiles for credential receivers.

Claims (80)

1 . A digital credential platform server configured to generate a model credential profile for particular field data objects, the digital credential platform server comprising:

a processing unit comprising one or more processors;

one or more network interfaces; and

memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the digital credential platform server to:

receive data identifying a first subset of credential receivers, out of a plurality of credential receivers associated with a field data object;

for each particular credential receiver in the first subset of credential receivers, determine a set of capabilities associated with the particular credential receiver, wherein determining set of capabilities comprises:

(a) retrieving one or more digital credentials issued to the particular credential receiver;

(b) retrieving data identifying one or more capabilities associated with each of the digital credentials issued to the particular credential receiver; and

(c) aggregating the capabilities associated with each of the digital credentials issued to the particular credential receiver;

perform an analysis on the determined sets of capabilities associated with each of the credential receivers in the first subset; and

generate a model capabilities profile for the field data object, based on the analysis of the determined sets of capabilities associated with each of the credential receivers in the first subset.

2 . The digital credential platform server of claim 1 , wherein performing the analysis on the determined sets of capabilities associated with the credential receivers in the first subset comprises performing at least one of a regression analysis or a machine learning algorithm on the aggregated capabilities data, to determine one or more correlations between the capabilities of the first subset of credential receivers.

3 . The digital credential platform server of claim 1 , wherein determining the set of capabilities associated with each particular credential receiver comprises determining, for each particular credential receiver in the first subset of credential receivers:

a plurality of capabilities associated with the particular credential receiver; and

a magnitude value for each of the plurality of capabilities associated with the particular credential receiver.

4 . The digital credential platform server of claim 1 , wherein determining the set of capabilities associated with each particular credential receiver further comprises, for each particular credential receiver in the first subset of credential receivers:

monitoring a physical environment associated with the particular credential receiver using a plurality of sensors, and detecting a plurality of user activities of the particular credential receiver within the physical environment; and

determining a plurality of capabilities associated with the particular credential receiver, based on the detected user activities of the particular credential receiver within the physical environment.

5 . The digital credential platform server of claim 1 , the memory storing additional instructions which, when executed by the processing unit, causes the digital credential platform server to:

for each particular credential receiver in the first subset of credential receivers, determine a set of traits associated with the particular credential receiver; and

perform an additional analysis of the determined sets of traits associated with each of the credential receivers in the first subset,

wherein generating the model capabilities profile for the field data object includes determining a model set of traits, based on the additional analysis of the determined sets of traits associated with each of the credential receivers in the first subset.

6 . The digital credential platform server of claim 1 , the memory storing additional instructions which, when executed by the processing unit, causes the digital credential platform server to:

for each particular credential receiver in the first subset of credential receivers, determine a set of physical condition traits associated with the particular credential receiver; and

perform an additional analysis of the determined sets of physical condition traits associated with each of the credential receivers in the first subset,

wherein generating the model capabilities profile for the field data object includes determining a model set of physical condition traits, based on the additional analysis of the determined sets of physical condition traits associated with each of the credential receivers in the first subset.

7 . The digital credential platform server of claim 1 , the memory storing additional instructions which, when executed by the processing unit, causes the digital credential platform server to:

prior to determining the sets of capabilities associated with each credential receiver in the first subset of credential receivers, determine the first subset of credential receivers out of the plurality of credential receivers by:

receiving performance data for each of the plurality of credential receivers, corresponding to the performance of the credential receivers with respect to a field identified in the field data object; and

selecting the first subset of credential receivers out of the plurality of credential receivers, based on the performance data.

8 . A method of generating a model credential profile for particular field data objects, comprising:

receiving, by a digital credential platform server, data identifying a first subset of credential receivers, out of a plurality of credential receivers associated with a field data object;

for each particular credential receiver in the first subset of credential receivers, determining a set of capabilities associated with the particular credential receiver, wherein determining set of capabilities comprises:

(a) retrieving, by the digital credential platform server, one or more digital credentials issued to the particular credential receiver;

(b) retrieving, by the digital credential platform server, data identifying one or more capabilities associated with each of the digital credentials issued to the particular credential receiver; and

(c) aggregating, by the digital credential platform server, the capabilities associated with each of the digital credentials issued to the particular credential receiver;

performing, by the digital credential platform server, an analysis on the determined sets of capabilities associated with each of the credential receivers in the first subset; and

generating, by the digital credential platform server, a model capabilities profile for the field data object, based on the analysis of the determined sets of capabilities associated with each of the credential receivers in the first subset.

9 . The method of claim 8 , wherein performing the analysis on the determined sets of capabilities associated with the credential receivers in the first subset comprises performing at least one of a regression analysis or a machine learning algorithm on the aggregated capabilities data, to determine one or more correlations between the capabilities of the first subset of credential receivers.

10 . The method of claim 8 , wherein determining the set of capabilities associated with each particular credential receiver comprises determining, for each particular credential receiver in the first subset of credential receivers:

a plurality of capabilities associated with the particular credential receiver; and

a magnitude value for each of the plurality of capabilities associated with the particular credential receiver.

11 . The method of claim 8 , wherein determining the set of capabilities associated with each particular credential receiver further comprises, for each particular credential receiver in the first subset of credential receivers:

monitoring a physical environment associated with the particular credential receiver using a plurality of sensors, and detecting a plurality of user activities of the particular credential receiver within the physical environment; and

determining a plurality of capabilities associated with the particular credential receiver, based on the detected user activities of the particular credential receiver within the physical environment.

12 . The method of claim 8 , further comprising:

for each particular credential receiver in the first subset of credential receivers, determining a set of traits associated with the particular credential receiver; and

performing an additional analysis of the determined sets of traits associated with each of the credential receivers in the first subset,

wherein generating the model capabilities profile for the field data object includes determining a model set of traits, based on the additional analysis of the determined sets of traits associated with each of the credential receivers in the first subset.

13 . The method of claim 8 , further comprising:

for each particular credential receiver in the first subset of credential receivers, determining a set of physical condition traits associated with the particular credential receiver; and

performing an additional analysis of the determined sets of physical condition traits associated with each of the credential receivers in the first subset,

wherein generating the model capabilities profile for the field data object includes determining a model set of physical condition traits, based on the additional analysis of the determined sets of physical condition traits associated with each of the credential receivers in the first subset.

14 . The method of claim 8 , further comprising:

prior to determining the sets of capabilities associated with each credential receiver in the first subset of credential receivers, determining the first subset of credential receivers out of the plurality of credential receivers by:

receiving performance data for each of the plurality of credential receivers, corresponding to the performance of the credential receivers with respect to a field identified in the field data object; and

selecting the first subset of credential receivers out of the plurality of credential receivers, based on the performance data.

15 . A non-transitory computer-readable medium, having instructions stored therein, which when executed by a computing device cause the computing device to perform a set of operations comprising:

receiving data identifying a first subset of credential receivers, out of a plurality of credential receivers associated with a field data object;

for each particular credential receiver in the first subset of credential receivers, determining a set of capabilities associated with the particular credential receiver, wherein determining set of capabilities comprises:

(a) retrieving one or more digital credentials issued to the particular credential receiver;

(b) retrieving data identifying one or more capabilities associated with each of the digital credentials issued to the particular credential receiver; and

(c) aggregating the capabilities associated with each of the digital credentials issued to the particular credential receiver;

performing an analysis on the determined sets of capabilities associated with each of the credential receivers in the first subset; and

generating a model capabilities profile for the field data object, based on the analysis of the determined sets of capabilities associated with each of the credential receivers in the first subset.

16 . The non-transitory computer-readable medium of claim 15 , wherein performing the analysis on the determined sets of capabilities associated with the credential receivers in the first subset comprises performing at least one of a regression analysis or a machine learning algorithm on the aggregated capabilities data, to determine one or more correlations between the capabilities of the first subset of credential receivers.

17 . The non-transitory computer-readable medium of claim 15 , wherein determining the set of capabilities associated with each particular credential receiver comprises determining, for each particular credential receiver in the first subset of credential receivers:

a plurality of capabilities associated with the particular credential receiver; and

a magnitude value for each of the plurality of capabilities associated with the particular credential receiver.

18 . The non-transitory computer-readable medium of claim 15 , wherein determining the set of capabilities associated with each particular credential receiver further comprises, for each particular credential receiver in the first subset of credential receivers:

monitoring a physical environment associated with the particular credential receiver using a plurality of sensors, and detecting a plurality of user activities of the particular credential receiver within the physical environment; and

determining a plurality of capabilities associated with the particular credential receiver, based on the detected user activities of the particular credential receiver within the physical environment.

19 . The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the computing device to perform operations comprising:

for each particular credential receiver in the first subset of credential receivers, determining a set of traits associated with the particular credential receiver; and

performing an additional analysis of the determined sets of traits associated with each of the credential receivers in the first subset,

wherein generating the model capabilities profile for the field data object includes determining a model set of traits, based on the additional analysis of the determined sets of traits associated with each of the credential receivers in the first subset.

20 . The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the computing device to perform operations comprising:

for each particular credential receiver in the first subset of credential receivers, determining a set of physical condition traits associated with the particular credential receiver; and

performing an additional analysis of the determined sets of physical condition traits associated with each of the credential receivers in the first subset,

wherein generating the model capabilities profile for the field data object includes determining a model set of physical condition traits, based on the additional analysis of the determined sets of physical condition traits associated with each of the credential receivers in the first subset.

Assignments (2)
CORRECTIVE ASSIGNMENT TO CORRECT THE CONVEYING PARTY'S EXECUTION DATES PREVIOUSLY RECORDED ON REEL 046916 FRAME 0900. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT OF ASSIGNOR'S INTEREST. Recorded Sep 27, 2018
From: MERCURY, MARK; SCHMIDT, JARIN; PORTER, E. CLARKE; PASCALE, PETER; STOCKINGER, ANDY; LANCASTER, RON
To: PEARSON EDUCATION, INC.
Reel/Frame 047158/0832 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 19, 2018
From: MERCURY, MARK; SCHMIDT, JARIN; PORTER, E. CLARKE; PASCALE, PETER; STOCKINGER, AMY; LANCASTER, RON
To: PEARSON EDUCATION, INC.
Reel/Frame 046916/0900 →