Privacy sensitive persona management tools

• US 9,875,490 B2
• Filed: 05/04/2016
• Issued: 01/23/2018
• Est. Priority Date: 05/16/2013
• Status: Expired due to Fees

• Current Assignee: Rally AG LLC (Teledisc Corporation)
• Original Assignee: AutoGraph Incorporated
• Inventors: Roundtree, Brian
• Primary Examiner(s): To, Baotran N
• Application Number:
  US15/146,860
• Publication Number:
  US 20160247206A1
• Time in Patent Office: 629 Days
• Field of Search: 726 28
• 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:

memory for storing instructions that are executable by processor electronics and data that is accessible by users;

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

configure a first private partition in the memory to store customer data that is accessible by a first user and not by a second user;

configure a second private partition in the memory to store customer data that is accessible by the second user and not by the first user;

create a first generic data partition by analyzing the customer data in the first partition and removing identifying data, wherein the first generic data partition is configured to exclude second user access;

determine if there would be an increase in the detail of the customer data in the first private partition if customer data in the first private partition were integrated with at least a portion of the customer data in the second partition; and

in response to a determination that there would be an increase in the detail of customer data in the first private partition, configure the first generic data partition to be accessible by the second user in exchange for the integration of at least some of the customer data in the second partition with the customer data in the first partition.

2. The system of claim 1, wherein the memory stores instructions that cause the processor electronics to determine that there is an increase in the customer detail in the first private partition if the portion of the customer data in the second partition includes:

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

or

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 the memory stores instructions that cause the processor electronics to determine that there is an increase in the customer detail in the first private partition if the portion of customer data in the second partition includes:

additional data that is similar in value to that of the customer data in the first private partition;

or

data based on a larger number of customers in comparison to the number of customers represented by the customer data in the first private partition.

4. The system of claim 1, wherein the memory stores instructions that cause the processor electronics to determine that there is an increase in the customer detail in the first private partition if the portion of the customer data in the second partition includes:

unrelated customer data to that in the first private partition.

5. The system of claim 1, wherein the memory stores instructions that cause the processor electronics to create the first generic partition by:

finding customer data in the first private partition and in the second private partition that share a common tag, wherein the common tags are associated with probabilities;

combining the associated probabilities associated to each common tag and grouping together data associated to each common tag; and

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

6. The system of claim 1, wherein the memory stores instructions that cause the processor electronics to remove identifying data by:

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

substituting generic marketing data with substantially similar associated probabilities for the identifying customer data.

7. The system of claim 1, wherein the memory stores instructions that cause the processor electronics 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 memory stores instructions that cause the processor electronics to create a relationship link between data associated with 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 memory stores instructions that cause the processor electronics to create a relationship link between data associated with 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 customer data in the first private partition is comprised of:

a user characteristic and 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 customer data in the first private partition is comprised of:

a user characteristic and a statistical probability associated with said user characteristic.

12. A processor-based system, comprising:

memory for storing instructions that are executable by processor electronics and customer data that is accessible by a user; and

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

determine generic customer data by;

finding customer data in a first data partition and the customer data in another data partition that are in common between the partitions, wherein the common customer data are associated with probabilities;

combining the associated probabilities between common customer data from the partitions; and

selecting the customer data, that are in both the first partition and the other data partition and any associated combined probabilities as the generic customer data.

13. The system of claim 12, further comprising instructions that are executable by the processor electronics to create a generic data partition comprised of the generic customer data.

14. The system of claim 13, further comprising instructions executable by the processor electronics to create a relationship link between customer data associated with a tag in the first data partition and data associated with a similar tag in the generic data partition.

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

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

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

a user characteristic and a statistical probability associated with said user characteristic.

17. A processor-based system, comprising:

memory for storing instructions that are executable by processor electronics;

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

upload customer data comprised of tags and associated statistical probabilities to a private partition on a remote device;

instruct the remote device to configure the private partition to prevent access to customer data in the partition; and

instruct the remote device to allow access to the customer data in the private partition by a user in response to the user offering offer data if the offer data is comprised of;

generic customer data from which identifying data has been removed.

18. The system of claim 17, wherein the customer data in the private partition includes:

a tag representing an end user characteristic; and

a statistical probability associated with said end user characteristic, said end user characteristic and statistical probability based at least upon user input.

19. The system of claim 17, wherein the customer data in the private partition includes:

a tag representing an end user characteristic; and

a statistical probability associated with said end user characteristic.

20. The system of claim 17, wherein the customer data in the private partition further includes data based as least on customer communication messages.