Privacy sensitive persona management tools

• US 9,348,979 B2
• Filed: 05/16/2014
• Issued: 05/24/2016
• Est. Priority Date: 05/16/2013
• Status: Active Grant

• Current Assignee: Rally AG LLC (Teledisc Corporation)
• Original Assignee: AutoGraph Incorporated
• Inventors: Roundtree, Brian
• Primary Examiner(s): To, Baotran N
• Application Number:
  US14/280,480
• Publication Number:
  US 20140344953A1
• Time in Patent Office: 739 Days
• Field of Search: 726/28
• US Class Current: 1/1
• CPC Class Codes: G06F 21/10 Protecting distributed programs or content, e.g. vending or licensing of copyrighted material protection in video systems or pay television H04N7/16 ; Digital rights management [DRM]
• CPC Class Codes: G06F 21/604 Tools and structures for managing or administering access control systems
• CPC Class Codes: G06F 21/6218 to a system of files or objects, e.g. local or distributed file system or database
• CPC Class Codes: G06F 21/6263 during internet communication, e.g. revealing personal data from cookies
• CPC Class Codes: G06F 2221/2117 User registration
• CPC Class Codes: G06F 2221/2141 Access rights, e.g. capability lists, access control lists, access tables, access matrices
• CPC Class Codes: G06F 2221/2149 Restricted operating environment
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: H04L 63/0421 Anonymous communication, i.e. the party's identifiers are hidden from the other party or parties, e.g. using an anonymizer
• CPC Class Codes: H04L 63/102 Entity profiles

Abstract

The disclosed tools include enhanced and flexible tools to enable users who may be business competitors to share non-generic data in a substantially generic and in a substantially equitable manner. The resulting incentive to more freely share data between competitors will benefit users such as brand owners and enhance content delivered to their end users based on shared data.

Claims

1. A processor-based system, comprising:

a. memory for storing instructions that are executable by processor electronics;

b. the processor electronics configured to execute the instructions in order to;

i. configure a first private partition to be accessible to a first user and not a second user;

ii. configure a second private partition to be accessible by the second user and not the first user;

iii. remove identifying data from at least a portion of the first private partition and put the remaining generic data into a first generic data partition configured to exclude second user access;

iv, determine if an offer from the second user to allow access to at least a portion of data in the second private partition or data based at least on the portion of the second private partition would result in an increase of first private partition data detail if the portion of data in the second private partition or data based at least on the portion of the second private partition were integrated with data in the first private partition; and

v. in response to a determination of first private partition data detail increase, configure second user access to the first generic data partition in exchange for first user access to the offered data.

2. The system of claim 1, wherein an increase in first private partition detail occurs if the offered data comprises:

i. a different data category than those in the first private partition;

or

ii at least one category with a larger amount of data in comparison to the amount of data of the same category in the first private partition.

3. The system of claim 1, wherein an increase in first private partition detail occurs if the offered data comprises:

i. a similar quantity of data to that in the first private partition;

or

ii. data based on a larger number of users in comparison to the number the data in the first private partition is based on.

4. The system of claim 1, wherein an increase in first private partition detail occurs if the offered data comprises:

i. unrelated data to that in the first private partition;

or

ii. related data to that in the first private partition.

5. The system of claim 1, wherein removing identifying data in the portion of the first private partition comprises the steps of:

a. finding data in the first private partition and in third partition sharing a common tag, wherein the common tags are associated to probabilities;

b. combining the associated probabilities associated to each common tag; and

c. separating generic data from non-generic data in said grouped data, wherein the generic data are the common tags and combined probabilities.

6. The system of claim 1, wherein removing identifying data comprises the steps of:

a. determining identifying data by cross referencing data in the portion of the first private partition with non-generic marketing data; and

b. substituting for the identifying data, generic marketing data with similar associated probabilities.

7. The system of claim 1, wherein the processor electronics is further configured to calculate a new data partition based on the first generic data partition and the second private partition.

8. The system of claim 1, wherein the processor electronics is further configured to create a relationship link between data associated to a tag in the first private partition and data associated with a similar tag in the second private partition.

9. The system of claim 1, wherein the processor electronics is further configured to create a relationship link between data associated to a tag in the first private partition and data associated with a similar tag in the first generic data partition.

10. The system of claim 1, wherein the data in the first private partition is comprised of:

1) a user characteristic; and

     2) a statistical probability associated with said user characteristic, said user characteristic and statistical probability based at least upon a user content affinity input.

11. The system of claim 1, wherein the data in the first private partition is comprised of:

1) a user characteristic; and

     2) a statistical probability associated with said user characteristic, wherein the user characteristic and statistical probability are configurable as components in an interest graph in which the user characteristic is represented as an interest graph node and the statistical probability is represented as an interest graph link connecting the interest graph node to another interest graph node.

12. A processor-based system, comprising;

a. memory for storing instructions that are executable by processor electronics; and

b. the processor electronics configured to execute the instructions in order to;

i. separate identifying data from at least a portion of a data partition by;

1. finding data in the portion of the data partition and another partition that share a common tag, wherein the common tags are associated to probabilities;

2. combining the associated probabilities and data associated to them between data from the portion of the data partition with the other partition that share a common tag;

3. separate portions of generic data from portions of non-generic data in the combined data, wherein the portions of generic data is data that is common between both the portion of the data partition and the other partition has in each combined tag grouping and their combined probabilities; and

ii. create a generic data partition comprised of the portions of generic data.

13. The system of claim 12, wherein the processor electronics is further configured to calculate a new data partition based on the generic partition and the data partition.

14. The system of claim 12, wherein the processor electronics is further configured to create a relationship link between data associated to a tag in the data partition and data associated with a similar tag in the generic data partition.

15. The system of claim 12, wherein data in the data partition is comprised of:

1) a user characteristic; and

     2) a statistical probability associated with said user characteristic, said user characteristic and statistical probability based at least upon a user content affinity input.

16. The system of claim 12, wherein data in the data partition is comprised of:

1) a user characteristic; and

     2) a statistical probability associated with said user characteristic, wherein the user characteristic and statistical probability are configurable as components in an interest graph in which the user characteristic is represented as an interest graph node and the statistical probability is represented as an interest graph link connecting the interest graph node to another interest graph node.