Television viewer profile initializer and related methods

• US 20020116710A1
• Filed: 02/22/2001
• Published: 08/22/2002
• Est. Priority Date: 02/22/2001
• Status: Abandoned Application

• Current Assignee: Philips Electronics North America Corporation (Koninklijke Philips N.V.)
• Original Assignee: Philips Electronics North America Corporation (Koninklijke Philips N.V.)
• Inventors: Rankin, Paul John, Schaffer, James David, Mathias, Keith, Milanski, John
• Application Number:
  US09/791,999
• Publication Number:
  US 20020116710A1
• Time in Patent Office: Days
• US Class Current: 725/46
• CPC Class Codes: H04H 60/66 for using the result on distributors' side
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• 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 21/4147 PVR [Personal Video Recorder] H04N5/76 takes precedence ; arrangements for broadcast with accumulation-type receivers H04H20/40
• 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 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/47 End-user applications
• CPC Class Codes: H04N 7/16 Analogue secrecy systems; Analogue subscription systems

Abstract

A TV viewer profile initializer for reducing the time it takes for an implicit profiler-based TV recommender to produce accurate TV recommendations. The profiles initializer utilizes stereotype profiles from a substantial pool of TV viewing behavior of a representative number of TV viewers. By applying clustering methods to such data, stereotype profiles can emerge. New viewers are then be offered a selection of stereotype profiles to choose from to initialize their own personal TV viewing profile. Thus, a single choice will suffice to provide a predictable TV show recommender that is presumably fairly close to a viewer'"'"'s own preferences. After this initialization, the profile can be adapted by the user'"'"'s own viewing behavior to migrate from the initial stereotype towards a more accurate profile of the user.

Claims

1. A method of initializing a recommender user'"'"'s personal behavior profile, the method comprising the steps of:

collecting behavioral data from a statistically significant number of individuals, the behavioral data being in the same domain as the recommender user'"'"'s personal behavior profile will be;

generating a plurality of stereotype behavior profiles from the behavioral data; and

selecting one of the stereotype behavior profiles that best represents the user'"'"'s behavior preferences, the selected stereotype behavior profile operating as the user'"'"'s initial personal behavior profile.

2. The method according to claim 1, wherein the step of generating a plurality of stereotype behavior profiles includes dividing the data according to intrinsic classes present in the data, the intrinsic classes defining the plurality of stereotypes.

3. The method according to claim 2, wherein the data is divided into the intrinsic classes by clustering the behavioral data.

4. The method according to claim 2, wherein the step of generating a plurality of stereotype behavior profiles further includes the step of deriving a stereotype behavior profile from a pseudo behavior history defined the data in each corresponding stereotype.

5. The method according to claim 4, wherein the pseudo behavior history is generated by applying a fixed threshold to the data in each of the classes, the fixed threshold including behavior from the class that defined the stereotype.

6. The method according to claim 5, wherein the step of generating a plurality of stereotype behavior profiles further includes the step of constructing a stereotype behavior profile from each pseudo behavior history.

7. The method according to claim 6, wherein the constructing step is performed with Bayesian classifiers.

8. The method according to claim 6, wherein the constructing step is performed with decision trees.

9. The method according to claim 4, wherein the pseudo behavior history is generated by scoring in proportion to representation in the class and adding a predetermined number of copies the behavior from the class that defined the stereotype to the pseudo view history.

10. The method according to claim 9, wherein the step of generating a plurality of stereotype behavior profiles further Includes the step of constructing a stereotype behavior profile from each pseudo behavior history.

11. The method according to claim 10, wherein the constructing step is performed with Bayesian classifiers.

12. The method according to claim 10, wherein the constructing step is performed with decision trees.

13. The method according to claim 1, wherein the stereotype behavior profiles are built from the behavior and non-behavior of the individuals.

14. The method according to claim 1, further comprising the step of tailoring the selected stereotype behavior profile into a more accurate profile of the user'"'"'s own behavior using the user'"'"'s own behavior.

15. The method according to claim 1, wherein the behavior is in the domain of television viewing.

16. The method according to claim 1, wherein the behavior is in the domain of multimedia viewing.

18. The profile initializer according to claim 17, further comprising a stereotype generator for generating behavior stereotypes from the behavioral data stored in the behavior database, wherein the stereotype profiler uses pseudo behavior histories obtained from the behavior stereotypes for building the stereotype behavior profiles.

19. The profile initializer according to claim 17, wherein the behavior is in the domain of television viewing.

20. The profile initializer according to claim 17, wherein the behavior is in the domain of multimedia viewing.

17. A profile initializer for a behavior recommender, the profile initializer comprising:

a behavior database for storing behavioral data of a statistically significant number of individuals; and

a stereotype profiler for building a selection of stereotype behavior profiles from the behavioral data, the stereotype behavior profiles for offering to a user of the recommender to initialize the user'"'"'s personal behavior profile.

21. An adaptive behavior recommender comprising:

a behavior database for storing behavioral data of a statistically significant number of individuals;

a stereotype profiler for building a selection of stereotype behavior profiles from the behavioral data, the stereotype behavior profiles being offered to a user of the recommender for initializing the user'"'"'s personal behavior profile; and

a recommender for making behavior recommendations based on the user'"'"'s selected stereotype behavior profile.

22. The behavior recommender according to claim 21, further comprising a user interface for displaying the behavior recommendations.

23. The behavior recommender according to claim 21, further comprising a stereotype generator for generating behavior stereotypes from the behavioral data stored in the behavior database, wherein the stereotype profiler uses pseudo behavior histories obtained from the behavior stereotypes for building the stereotype behavior profiles.

24. The behavior recommender according to claim 21, further comprising a personal profiler for tailoring the user selected stereotype behavior profile into a personal profile of the user'"'"'s behavior using the actual behavior of the user.

25. The behavior recommender according to claim 21, wherein the behavior is in the domain of television viewing.

26. The behavior recommender according to claim 21, wherein the behavior is in the domain of multimedia viewing.