Personalized content distribution

Patent metadata

Field	Value
Publication number	US-10949763-B2
Application number	US-201715442325-A
Country	US
Kind code	B2
Filing date	Feb 24, 2017
Priority date	Apr 8, 2016
Publication date	Mar 16, 2021
Grant date	Mar 16, 2021

Abstract

Systems and methods for content provisioning are disclosed herein. The system can include memory having a content database, a task database, and a user profile database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include a server that can: receive a user identifier from the user device; retrieve user information from the user profile database, which user information identifies one or several attributes of the user; retrieve user task data from the task database, which user task data identifies a plurality of tasks for completion by the user; automatically generate prioritization data for the plurality of tasks identified by the user task data; select a task based on the prioritization data; and send content relating to the selected task to the user device.

First claim

What is claimed is:

1. A system for content provisioning, the system comprising:
memory comprising:
a content database comprising content for delivery to a user;
a task database comprising data identifying a plurality of tasks; and
a user profile database comprising information identifying one of several attributes of the user;
a user device comprising:
a first network interface configured to exchange data via a communication network; and
a first I/O subsystem configured to convert electrical signals to user interpretable outputs via a user interface; and

one or several servers, wherein the one or several servers are configured to:
receive a user identifier from the user device;
retrieve user information from the user profile database, wherein the user information identifies one or several attributes of the user;
retrieve user task data from the task database, wherein the user task data identifies a plurality of tasks for completion by the user;
automatically generate dynamic relative prioritization data for the plurality of tasks based on the results of one or several user completed tasks selected from the tasks associated with a course, group, or class;
select a task based on the prioritization data;
determine a user mastery level associated with the task;
identify content having a difficulty level corresponding to the user mastery level, by:
determining a likelihood of the user correctly responding to the content, and
determining that the likelihood of the user correctly responding to the content exceeds a first threshold value and is less than a second threshold value; and

send the content relating to the selected task to the user device.

2. The system of claim 1 , wherein generating prioritization data comprises:
receiving a prioritization request;
identifying a task set from the plurality of tasks stored in the task database, wherein the task set comprises a plurality of tasks;
creating a weighted delta value based on one or more attributes of the user; and
sorting the tasks according to the weighted delta value.

3. The system of claim 2 , wherein generating prioritization data further comprises:
identifying a user attribute from the retrieved user information wherein a user attribute comprises one or more skills associated with user interactions with content relating to the task;
identifying attributes of the plurality of tasks forming the task set; and
generating a delta value for each of at least some of the plurality of tasks forming the task set, wherein the delta value characterizes a difference between the identified user attribute and the identified attribute for the task for which the delta value is generated.

4. The system of claim 3 , wherein the attributes of the plurality of tasks comprise a difficulty level identifying a skill level requisite to successfully complete an associated task.

5. The system of claim 4 , wherein the difference between the identified user attribute and the identified attribute for the task characterized by the delta value is the difference between a skill level of the user and the difficulty level of the task characterized by the delta value.

6. The system of claim 3 , wherein the one or several servers are further configured to weight each of the delta values according to a contribution value characterizing the relative import of the task characterized by the delta value.

7. The system of claim 6 , wherein the one or several servers are further configured to sort the tasks associated with the weighted delta values according to the weighted delta value associated with each of the tasks.

8. A method for content provisioning comprising:
receiving a user identifier from a user device at one or several servers;
retrieving with the one or several servers user information from a user profile database comprising information identifying one of several attributes of a user, wherein the user information identifies one or several attributes of the user;
retrieving with the one or several servers user task data from a task database comprising data identifying a plurality of tasks, wherein the user task data identifies a plurality of tasks for completion by the user;
automatically generating dynamic relative prioritization data for the plurality of tasks based on the results of one or several user completed tasks selected from the tasks associated with a course, group, or class;
selecting with the one or several servers a task based on the prioritization data;
determining with the one or several servers a user mastery level associated with the task;
identifying with the one or several servers content having a difficulty level corresponding to the user mastery level, by:
determining with the one or several servers a likelihood of the user correctly responding to the content, and
determining with the one or several servers that the likelihood of the user correctly responding to the content exceeds a first threshold value or is less than a second threshold value; and

sending content relating to the selected task from the one or several servers to the user device.

9. The method of claim 8 , wherein generating prioritization data comprises:
receiving a prioritization request;
identifying a task set from the plurality of tasks stored in the task database, wherein the task set comprises a plurality of tasks;
creating a weighted delta value based on one or more attributes of the user, and
sorting the tasks according to the weighted delta value.

10. The method of claim 9 , wherein generating prioritization data further comprises:
identifying a user attribute from the retrieved user information wherein a user attribute comprises one or more skills associated with user interactions with content relating to the task;
identifying attributes of the plurality of tasks forming the task set; and
generating a delta value for each of at least some of the plurality of tasks forming the task set, wherein the delta value characterizes a difference between the identified user attribute and the identified attribute for the task for which the delta value is generated.

11. The method of claim 10 , wherein the attributes of the plurality of tasks comprise a difficulty level identifying a skill level requisite to successfully complete an associated task.

12. The method of claim 11 , wherein the difference between the identified user attribute and the identified attribute for the task characterized by the delta value is the difference between a skill level of the user and the difficulty level of the task characterized by the delta value.

13. The method of claim 10 , further comprising weighting each of the delta values according to a contribution value characterizing the relative import of the task characterized by the delta value.

14. The method of claim 13 , further comprising sorting the tasks associated with the weighted delta values according to the weighted delta value associated with each of the tasks.

Assignees

• Pearson Education Inc

Inventors

• Moriarty Brian
• Potter Mark

Classifications

• H04L12/4641 Primary

  Virtual LANs, VLANs, e.g. virtual private networks [VPN] (LAN interconnection over a bridge based backbone H04L12/462; encapsulation techniques H04L12/4633; routing of packets H04L45/00; packet switches H04L49/00; virtual private networks for security H04L63/0272) · CPC title

• G06N5/01

  Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• H04L47/10

  Flow control; Congestion control · CPC title

• G06N5/022

  Knowledge engineering; Knowledge acquisition · CPC title