Granted Patent B2

US 12,328,465 · App. 18/130,868 · Granted Jun 10, 2025

Inventors: Peter Docherty (Glasgow, GB); Christopher McGuire (Glasgow, GB); Edward Young (Glasgow, GB)

Assignee: ThinkAnalytics Ltd.

H04N21/25891G06Q30/0269H04N21/252H04N21/25841H04N21/2668H04N21/44222H04N21/4532H04N21/4661H04N21/4665H04N21/4667H04N21/4668H04N21/482H04N21/8126

Abstract

Claims (45)

1. A computer-implemented method of determining affinity profiles, comprising:

providing television content to each of a plurality of user devices using a content distribution system,

wherein each user device displays an electronic programme guide (EPG) or other user interface that is operable by a user to select one or more items of television content, and

wherein in response to the selections, the content distribution system distributes the selected items of television content to the user device for viewing or other consumption by the user during content viewing sessions;

for each of the plurality of user devices, monitoring user activity including identifying the selected items of television content;

obtaining metadata concerning the selected items of television content, the metadata representing at least some properties of the selected items of television content;

generating or updating a user record for the user, the user record comprising or representing at least one of the user activity or the associated content metadata; and

processing the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one of a selected affinity category or an affinity category score,

wherein the selected affinity category is selected from a stored set of affinity categories, each of the stored set of affinity categories representing an affinity of the user for a respective subject area,

wherein the metadata concerning the selected items of television content is obtained from a stored ontology that includes at least 10,000 features that can be used as metadata to represent the selected items of television content,

wherein the processing of the user record to generate the affinity profile comprises applying a mapping process to map between the metadata in the user record and the affinity categories, and

wherein the mapping process includes applying weightings or confidence scores for mappings between the metadata in the user record and items in the affinity categories.

2. The method of claim 1 , wherein the generating of the affinity profiles comprises applying a machine learning model to the user record, the machine learning model being configured to output the affinity profile based on the user record.

3. The method of claim 2 , wherein the machine learning model comprises or uses a text classifier that is operable to receive text input relating to television content as part of the user record and to output the affinity profile.

4. The method of claim 3 , wherein the text classifier comprises a zero shot classifier.

5. The method of claim 1 , wherein the generating of the affinity profile is independent of, or is performed without taking into account, data representing socio-economic or demographic status of the user.

6. The method of claim 5 , wherein at least one of a), b) or c):

a) the user record for each user does not include any data representing socio-economic or demographic status of the user;

b) the user record for each user is anonymous; or

c) the obtaining of metadata, the generating or updating of the user records, and the processing of the user records to generate affinity profiles are performed by processing circuitry that does not have access to at least one of or all of data representing socio-economic or demographic status of the users or identity of the users.

7. The method of claim 1 , wherein the stored set of affinity categories comprises at least 100 affinity categories or sub-categories.

8. The method of claim 1 , wherein the ontology includes enriched versions of metadata obtained for items of television content.

9. The method of claim 1 , wherein the user record comprises or represents user activity for different time windows during a day or week, and the method comprises generating different affinity profiles for the user for the different time windows.

10. The method of claim 1 , further comprising categorizing the user into one of a plurality of categories based on the affinity profile.

11. The method of claim 1 , wherein at least one of:

the affinity profile for the user comprises a set of scores, each score being for a respective one of the affinity categories; or

the user is a user account.

12. The method according to claim 11 ,

wherein at least one of a plurality of individuals have access to the user account or a plurality of user devices are associated with the user account, and

wherein the affinity profile for the user account is based on at least one of selection of television content by the plurality of individuals or using the plurality of user devices.

13. The method according to claim 1 , further comprising selecting additional television content to push to the user based on the determined affinity profile for the user.

14. The method according to claim 1 , further comprising outputting the determined affinity profiles for the plurality of users via an API or operator interface thereby making the affinity profiles available to a third party external to the content distribution system.

15. A system comprising processing circuitry configured to:

provide television content to each of a plurality of user devices using a content distribution system,

wherein each user device displays an electronic programme guide (EPG) or other user interface that is operable by a user to select one or more items of television content, and

wherein in response to the selections, the content distribution system distributes the selected items of television content to the user device for viewing or other consumption by the user during content viewing sessions;

for each of the plurality of user devices, monitor user activity including identifying the selected items of television content;

obtain metadata concerning the selected items of television content, the metadata representing at least some properties of the selected items of television content;

generate or update a user record for the user, the user record comprising or representing at least one of the user activity or the associated content metadata; and

process the user record to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one of a selected affinity category or an affinity category score,

wherein the selected affinity category is selected from a stored set of affinity categories, each of the stored set of affinity categories representing an affinity of the user for a respective subject area,

wherein the metadata concerning the selected items of television content is obtained from a stored ontology that includes at least 10,000 features that can be used as metadata to represent the selected items of television content,

wherein the processing of the user record to generate the affinity profile comprises applying a mapping process to map between the metadata in the user record and the affinity categories, and

wherein the mapping process includes applying weightings or confidence scores for mappings between the metadata in the user record and items in the affinity categories.

16. A non-transitory computer-readable medium that comprises computer-readable instructions that are executable to perform a method according to claim 1 .

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (84)

Cited By (4)

US 12,542,941 US 12,610,097 US 12,610,098 US 12,610,099