Method, system and program product for populating a user profile based on existing user profiles

• US 7,035,863 B2
• Filed: 06/19/2002
• Issued: 04/25/2006
• Est. Priority Date: 11/13/2001
• Status: Expired due to Term

• Current Assignee: Sisvel S.p.A. (Fineur International S.A.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Kurapati, Kaushal, Gutta, Srinivas
• Primary Examiner(s): Wassum, Luke S
• Assistant Examiner(s): Black, Linh
• Application Number:
  US10/175,193
• Publication Number:
  US 20030236770A1
• Time in Patent Office: 1,406 Days
• Field of Search: 707 1-1041, 705/26
• US Class Current: 707/737
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/454 Content or additional data filtering, e.g. blocking advertisements
• CPC Class Codes: H04N 21/4661 Deriving a combined profile for a plurality of end-users of the same client, e.g. for family members within a home user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/4755 for defining user preferences, e.g. favourite actors or genre retrieval personalisation and generation of user profiles for the retrieval of video data G06F16/739; user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 7/163 by receiver means only
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

A method, system and program product for populating a user profile based on existing user profiles is provided. Specifically, under the present invention, base characteristics are designated for a new user profile. Based on the designated characteristics, the new user profile is associated with a particular Vornoi cluster region of existing user profiles. Once associated, the new user profile is populated with defined characteristics from the existing user profiles within the particular cluster region. After population, viewing recommendations can be made.

Claims

1. A method for populating a user profile based on existing user profiles, comprising:

designating base characteristics for a new user profile;

associating the new user profile with a cluster region of existing user profiles based on the base characteristics; and

populating the new user profile with defined characteristics from the existing user profiles.

2. The method of claim 1, further comprising making a recommendation based on the populated new user profile.

3. The method of claim 1, further comprising providing a plurality of existing user profiles grouped into cluster regions, prior to the associating step.

4. The method of claim 3, wherein the cluster regions are Vornoi cluster regions in that an existing user profile in a particular cluster region is closer in proximity to other existing user profiles in the particular cluster region than it is to existing user profiles in other cluster regions.

5. The method of claim 1, wherein the associating step comprises:

comparing the base characteristics of the new user profile to defined characteristics of existing user profiles to identify existing user profiles that are similar to the new user profile; and

associating the new user profile with a cluster region having similar existing user profiles.

6. The method of claim 1, wherein the base characteristics and the defined characteristics comprise user preferences that are selected from the group consisting of programs, channels, actors and genres.

7. A method for populating a user profile based on existing user profiles, comprising:

providing a plurality of existing user profiles grouped into Vornoi clusters regions;

designating base characteristics for a new user profile;

associating the new user profile with one of the Vornoi cluster regions based on the base characteristics; and

populating the new user profile with defined characteristics from the existing user profiles.

8. The method of claim 7, further comprising making a recommendation based on the populated user profile.

9. The method of claim 7, wherein the associating step comprises:

comparing the base characteristics of the new user profile to defined characteristics of existing user profiles to identify existing user profiles that are similar to the new user profile; and

associating the new user profile with a cluster region having similar existing user profiles.

10. The method of claim 7, wherein the base characteristics and the defined characteristics comprise user preferences that are selected from the group consisting of programs, channels, actors and genres.

11. A computer implemented system for populating a user profile based on existing user profiles, comprising a memory containing:

a designation system for designating base characteristics for a new user profile;

an association system for associating the new user profile with a cluster region of existing user profiles based on the base characteristics; and

a population system for populating the new user profile with defined characteristics from the existing user profiles.

12. The system of claim 11, further comprising a recommendation system for making a recommendation based on the populated new user profile.

13. The system of claim 11, further comprising a cluster system for grouping a plurality of existing user profiles into cluster regions.

14. The system of claim 13, wherein the cluster regions are Vornoi cluster regions in that an existing user profile in a particular cluster region is closer in proximity to other existing user profiles in the particular cluster region than it is to existing user profiles in other cluster regions.

15. The system of claim 11, wherein the association system comprises a comparison system for comparing the base characteristics of the new user profile to defined characteristics of existing user profiles to identify existing user profiles that are similar to the new user profile.

16. The system of claim 11, wherein the base characteristics and the defined characteristics comprise user preferences that are selected from the group consisting of programs, channels, actors and genres.

17. A program product stored on a recordable medium for populating a user profile based on existing user profiles, which when executed, comprises:

program code for designating base characteristics for a new user profile;

program code for associating the new user profile with a cluster region of existing user profiles based on the base characteristics; and

program code for populating the new user profile with defined characteristics from the existing user profiles.

18. The program product of claim 17, further comprising program code for making a recommendation based on the populated new user profile.

19. The program product of claim 17, further comprising program code for grouping a plurality of existing user profiles into cluster regions.

20. The program product of claim 19, wherein the cluster regions are Vornoi regions in that an existing user profile in a particular cluster region is closer in proximity to other existing user profiles in the particular cluster region than it is to existing user profiles in other cluster regions.

21. The program product of claim 17, wherein the program code for associating comprises program code for comparing the base characteristics of the new user profile to defined characteristics of existing user profiles to identify existing user profiles that are similar to the new user profile.

22. The program product of claim 17, wherein the base characteristics and the defined characteristics comprise user preferences that are selected from the group consisting of programs, channels, actors and genres.