Content delivery system

Patent metadata

Field	Value
Publication number	US-10891344-B2
Application number	US-201515523079-A
Country	US
Kind code	B2
Filing date	Oct 29, 2015
Priority date	Oct 31, 2014
Publication date	Jan 12, 2021
Grant date	Jan 12, 2021

Abstract

There is disclosed a content delivery computer system arranged to recommend content items to a user of the system having at least one predetermined characteristic, the content delivery system comprising: a social media analyser configured to receive and analyse social media communications from multiple consumers; a grouping component for grouping at least some of the consumers according to the analysed social media communications into respective groups; and a recommendation module configured to receive the at least one predetermined characteristic of the user, compare it with group characteristics of the respective groups to identify a group that shares the at least one predetermined characteristic, and generate a recommendation comprising one of more selected content items for the user based on the identified group of consumers; and an interface for delivering the recommendation to the user.

First claim

The invention claimed is:

1. A content delivery system arranged to recommend content items to a user of the content delivery system having at least one predetermined characteristic, the content delivery system comprising:
a social media analyser stored in a memory of the system and implemented by a processor, the social media analyser configured to receive and analyse social media communications from multiple consumers including users of the content delivery system and non-users of the content delivery system;
a dynamic grouping component stored in the memory of the system and implemented by the processor, the dynamic grouping component configured to dynamically group at least some of the consumers, including the non-users of the content delivery system, according to the analysed social media communications, into dynamically created respective groups;
a user matching module stored in the memory of the system and implemented by the processor, the user matching module configured to receive the at least one predetermined characteristic of the user of the content delivery system, compare it with group characteristics of the respective groups to identify a group that shares the at least one predetermined characteristic, and allocate the user of the content delivery system to one or more of the respective groups, wherein the allocating process at one time instant yields different results to the allocating process at a different time instant; and
a recommendation engine stored in the memory of the system and implemented by the processor, the recommendation engine configured to generate a recommendation of one or more selected content items for the user of the content delivery system based on the one or more respective dynamic groups to which the user of the content delivery system is instantaneously allocated, whereby the recommendation for the user of the content delivery system is based on social media communications of multiple consumers including non-users of the content delivery system; and
an interface for delivering the recommendation to the user of the content delivery system.

2. The content delivery computer system of claim 1 wherein the dynamic grouping component groups all the consumers including non-users of the content delivery system associated with determined relevant social media communications.

3. The content delivery computer system of claim 1 wherein the dynamic grouping component is configured to group the at least some of the consumers including non-users of the content delivery system in dependence on an analysis of message content associated with their social media communications.

4. The content delivery computer system of claim 1 wherein the dynamic grouping component is configured to group the at least some of the consumers including non-users of the content delivery system in dependence on an analysis of their profile information.

5. The content delivery computer system of claim 1 wherein the dynamic grouping component is configured to group the at least some of the consumers including non-users of the content delivery system in dependence on an analysis of metadata associated with their social media communications.

6. A server comprising the content delivery computer system of claim 1 .

7. The server of claim 6 wherein the interface is a network interface for connecting the server to a network which is in communication with a user terminal.

8. The content delivery computer system of claim 1 wherein, responsive to the user of the content delivery system responding positively to a recommendation, the allocation of the user of the content delivery system to the respective group is reinforced.

9. The content delivery computer system of claim 1 wherein the user matching module is further configured to allocate the user of the content delivery system to one or more of the respective groups further in dependence on the context of the user of the content delivery system.

10. The content delivery computer system of claim 1 wherein the non-users of the content delivery system include members of the general public whose social media updates are publicly available.

11. A method of selecting content items to be delivered to a user of a content delivery system, the user having at least one predetermined characteristic, the method comprising:
receiving at the computer system social media communications from multiple consumers, the multiple consumers including users of the content delivery system and non-users of the content delivery system;
using a social media analytic program component executing at the computer system to automatically analyse the social media communications;
using a dynamic grouping program component executing at the computer system to dynamically group at least some of the consumers, including the non-users of the content delivery system, according to the analysed social media communications into respective groups;
storing in an electronic memory for each of the groups a set of group characteristics for that group;
comparing the at least one predetermined characteristic of the user of the content delivery system with the group characteristics to identify a group of consumers that shares the at least one predetermined characteristic;
allocating the user of the content delivery system to one or more of the respective groups, wherein allocating at one time instant yields different results to allocating at a different time instant;
generating a recommendation comprising one or more selected content items for the user of the content delivery system based on the one or more of the respective groups to which the user of the content delivery system is instantaneously allocated, whereby the recommendation for the user of the content delivery system is based on social media communications of the non-users of the content delivery system; and
delivering a content identifier identifying the one or more content items to the user of the content delivery system.

12. The method of claim 11 , further comprising:
dynamically grouping all the consumers associated with determined relevant social media communications.

13. The method of claim 11 , further comprising:
dynamically grouping at least some of the consumers in dependence on an analysis of message content associated with their social media communications.

14. The method of claim 11 , further comprising:
dynamically grouping at least some of the consumers in dependence on an analysis of their profile information.

15. The method of claim 11 , further comprising:
dynamically grouping at least some of the consumers in dependence on an analysis of metadata associated with their social media communications.

16. A computer program product embodied on a non-transitory computer-readable medium and configured so as when executed on a processor to perform the method of claim 11 .

17. A computer program embodied on a non-transitory computer-readable medium and, when executed on a processor, performs the method of claim 11 .

18. The method of claim 11 wherein, responsive to the user of the content delivery system responding positively to a recommendation, reinforcing the allocation of the user of the content delivery system to the respective group.

19. The method of claim 11 further comprising allocating the user of the content delivery system to one or more of the respective groups further in dependence on the context of the user of the content delivery system.

20. The method of claim 11 wherein the non-users of the content delivery system incl

Assignees

• Piksel Inc

Inventors

• Shaw Philip
• Maas Hans-Jurgen

Classifications

• G06F16/9535 Primary

  Search customisation based on user profiles and personalisation · CPC title

• G06F16/9536 Primary

  Search customisation based on social or collaborative filtering · CPC title

• G06Q50/00 Primary

  Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism (healthcare informatics G16H) · CPC title

• G06F16/958

  Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking · CPC title