METHOD AND SYSTEM FOR RECOMMENDING CONTENT ITEMS

• US 20100088649A1
• Filed: 03/07/2008
• Published: 04/08/2010
• Est. Priority Date: 03/31/2007
• Status: Active Grant

• Current Assignee: Sony Deutschland GmbH (Sony Group Corp.)
• Original Assignee: Sony Deutschland GmbH (Sony Group Corp.)
• Inventors: Kemp, Thomas
• Granted Patent: US 9,317,852 B2
• Time in Patent Office: Days
• US Class Current: 715/845
• CPC Class Codes: G06Q 30/00 Commerce

Abstract

A method for recommending content items of a content item data base to a user, including: broadcasting user group characteristics, wherein a respective user group characteristic is descriptive of a respective user group; receiving at a user'"'"'s location the user group characteristics; assigning at the user'"'"'s location the user to at least one of the user groups, providing user group preference data, the user group preference data being descriptive of a relation between the user groups and the content items; and recommending content items according to the user group preference data.

Claims

1. Method for recommending content items of a content item data base to a user, comprising:

broadcasting user group characteristics, wherein a respective user group characteristic is descriptive of a respective user group;

receiving at a user'"'"'s location said user group characteristics;

assigning at said user'"'"'s location said user to at least one of said user groups

providing user group preference data, said user group preference data being descriptive of a relation between said user groups and said content items; and

recommending content items according to said user group preference data.

2. Method according to claim 1, wherein said step of assigning comprises selecting one of said user groups by the user.

3. Method according to claim 1, further comprising:

evaluating a usage behavior of the user;

comparing said usage behavior with said user group characteristics;

wherein the step of assigning at least one of said broadcasted user groups comprises assigning the user group to the user, which user group characteristic corresponds to said usage behavior.

4. Method according to claim 1, wherein said user group characteristics are derived automatically by grouping probe users, who gave similar feedback to same content items.

5. Method according to claim 1, wherein said user group characteristics are derived by identifying correlated content items and finding probe users, who gave similar feedback to said correlated content items.

6. Method according to claim 4, further comprising:

adapting said user group characteristics according to further feedback, said further feedback being provided by said probe users; and

broadcasting said adapted user group characteristics to said user'"'"'s location.

7. Method according to claim 1, wherein said user group preference data is determined by assigning content item identifications of content items to said user groups.

8. Method according to claim 1, wherein said user group preference data is determined by assigning a user group identification to said content items and wherein said user group identification is transmitted with the content item to said user'"'"'s location.

9. Method according to claim 1, further comprising:

deriving user group descriptive meta data from said user group characteristics and broadcasting said user group meta data as said user group preference data;

deriving descriptive meta data for said content items;

comparing said user group descriptive meta data with said descriptive meta data; and

recommending content items with descriptive meta data, which is similar to the user group descriptive meta data of said assigned user group.

10. Method according to claim 9, wherein said descriptive meta data is transmitted from a content item data base to said user'"'"'s location.

11. Method according to claim 9, wherein said descriptive meta data is derived at the user'"'"'s location.

12. Method according to claim 1, wherein said user group characteristics comprises a hierarchical order with broad main user group characteristics and narrower sub-group characteristics and wherein said main user group characteristics are broadcasted before said sub-group characteristics.

13. Method according to claim 1, wherein said user group characteristics are broadcasted over a data channel used for broadcasting an electronic program guide.

14. Method according to claim 1, further comprising:

requesting said recommended content item from a content item data base; and

transmitting said requested content item to said user'"'"'s location.

15. A system for recommending content items of a content item data base to a user, comprising:

a broadcasting device, said broadcasting device being configured to broadcast user group characteristics, wherein a respective user group characteristic is descriptive of a respective user group, and user group preference data; and

a receiver, said receiver being configured to receive said broadcasted user group characteristics and said user group preference data, and said receiver comprising

a processor (402) configured to assign at least one of said user groups to said user and to recommend content items to said user according to said user group preference data.

16. System according to claim 15, wherein said receiver further comprises:

a display configured to display said user groups;

an input mechanism (406) configured to allow a selection of said user groups displayed on said display;

wherein said processor (400) is further configured to assign at least one of said transmitted user groups to the user by using said selection.

17. System according to claim 15, wherein said processor is further configured to evaluate a usage behavior of the user, to compare said usage behavior with said transmitted user group characteristics, and is further configured to assign the user group to the user, which user group characteristic correspond to said usage behavior.

18. System according to claim 15, wherein said broadcasting device further comprises:

a user group generator configured to derive said user group characteristics automatically by grouping probe users, who gave similar feedback to same content items.

19. System according to claim 15, wherein said broadcasting device further comprises:

a user group generator configured to derive said user group characteristics by identifying correlated content items and finding probe users, who gave similar feedbacks to said correlated content items.

20. System according to claim 18, wherein said user group generator is further configured to generate adapted user group characteristics based on on-going feedback of said probe users;

and wherein said broadcasting device (500) is configured to broadcast said adapted user group characteristics.

21. System according to claim 18, wherein said user group generator is further configured to determine said user group preference data by assigning content item identifications of content items to said user groups.

22. System according to claim 18, further comprising:

a content item data base, said content item data base being connected with said user group generator and being configured to determine said user group preference data by assigning a user group identification to said content items; and

a transmitter configured to transmit said user group identification with the content item to said receiver.

23. System according to claim 18,

wherein said user group generator is further configured to derive user group descriptive meta data from said user group characteristics;

wherein said broadcasting device is further configured to broadcast said user group descriptive meta data as said user group preference data; and

wherein said processor is configured to derive descriptive meta data for said content items, to compare said user group descriptive meta data with said descriptive meta data, and said processor is further configured to recommend content items with descriptive meta data, which is similar to the user group descriptive meta data of said assigned user group.

24. System according to claim 18, further comprising:

a content item data base, said content item data base being configured to store descriptive meta data for said content items, wherein said user group generator is further configured to derive user group descriptive meta data from said user group characteristics;

wherein said broadcasting device is further configured to broadcast said user group descriptive meta data as said user group preference data; and

wherein said processor is further configured to compare said user group descriptive meta data with said received descriptive meta data, and to recommend content items with descriptive meta data, which is similar to the user group descriptive meta data of said assigned user group.

25. System according to claim 15, further comprising

a data channel used for broadcasting an electronic program guide and for broadcasting said user group characteristic.

26. System according to claim 15, wherein said processor is configured to request a recommended content item from a content item data base, said system further comprising:

a transmitter configured to transmit said requested content item to said receiver.

27. A receiver for recommending content items of a content item data base to a user, said receiver being configured to receive broadcasted user group characteristics, wherein a respective user group characteristic is descriptive of a respective user group, and user group preference data, said receiver comprising:

a processor (402) configured to assign at least one of said user groups to said user and to recommend content items to said user according to said user group preference data.

28. Receiver according to claim 27, further comprising:

a display configured to display said user groups;

an input mechanism configured to allow a selection of said user groups displayed on said display;

wherein said processor is further configured to assign at least one of said transmitted user groups to the user by using said selection.

29. Receiver according to claim 27, said receiver is further configured to evaluate a usage behavior of the user, to compare said usage behavior with said transmitted user group characteristics, and to assign the user group to the user, which user group characteristic correspond to said usage behavior.

30. Receiver according to claim 27, wherein said processor is further configured to request said recommended content item from a content item data base.

31. Receiver according to claim 27, wherein said receiver is further configured to receive user group descriptive meta data and said processor is further configured to derive descriptive meta data for said content items, to compare said user group descriptive meta data with said content item descriptive meta data;

and is further configured to recommend content items with descriptive meta data, which is similar to the user group descriptive meta data of said assigned user group.

32. Receiver according to claim 27, wherein said receiver is further configured to receive descriptive meta data for said content items and to receive user group descriptive meta data;

and said processor is further configured to compare said user group descriptive meta data with said descriptive meta data; and

to recommend content items with descriptive meta data, which is similar to the user group descriptive meta data of said assigned user group.