Observation-based user profiling and profile matching

• US 8,156,064 B2
• Filed: 06/30/2008
• Issued: 04/10/2012
• Est. Priority Date: 07/05/2007
• Status: Active Grant

• Current Assignee: Invent.ly LLC
• Original Assignee: Stephen J Brown
• Inventors: Brown, Stephen J.
• Primary Examiner(s): Holmes, Michael B
• Application Number:
  US12/215,957
• Publication Number:
  US 20090012925A1
• Time in Patent Office: 1,380 Days
• Field of Search: 706/46
• US Class Current: 706/46
• CPC Class Codes: G06F 16/23 Updating
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Observation-based user profiling and profile matching are provided. The network behavior of users of a computer-implemented social network are observed and used for user profiling. By observing network behavior instead of necessarily relying on user self-reported data, accurate and objective user profiles can be formed; user profiling is accomplished based on the observed network behaviors with or without the knowledge of the user being profiled. The observed network behaviors can include the customization of a visual graphic, a media preference, a communication preference, or a selection of words from a word list. The user profiles can be with respect to a domain and two or more users can be matched based on their profiles with respect to the same domain. User ratings and profile updating based on the ratings are also provided.

Claims

1. A method of profile matching based on observed network behavior in a computer-implemented social network of a plurality of users, said method comprising:

(a) observing network behaviors of at least some of said plurality of users of said social network, called observed users, wherein said network behaviors of each of said observed users comprise;

(i) a customization of a visual graphic by the same of said observed users;

(ii) a media preference of the same of said observed users; and

(iii) a communication preference of the same of said observed users;

(b) profiling at least some of said observed users based on said observed network behaviors of the same of said observed users, wherein said profiling is with respect to one or more domains, wherein said profiling comprises associating one or more scale factors for each of said observed network behaviors based on a relevance of the same of said observed network behaviors to said domain used in said profiling;

(c) matching two or more of said profiled users with respect to the same of said domains, wherein said matching is based on said profiling;

(d) rating said profile matching based on one or more user inputs of said matched profiled users, a participation data of said matched profiled users, or any combination thereof; and

(e) updating said profiling by refining said scale factors based on said rating.

2. The method as set forth in claim 1, wherein said profiling comprises associating one or more scale factors for each of said observed network behaviors, and wherein said scale factor associating is based on a relevance of the same of said observed network behaviors to said domain used in said profiling.

3. The method as set forth in claim 1, wherein said visual graphic comprises an avatar, and wherein said customization comprises determining an appearance of said avatar.

4. The method as set forth in claim 1, wherein said media preference is associated with a media content, a media type, a frequency of media playback, or any combination thereof.

5. The method as set forth in claim 1, wherein said communication preference comprises a communication method, a communication timing, a communication frequency, or any combination thereof.

6. The method as set forth in claim 1, wherein one of said network behaviors comprises a selection of words from a word list by one of said observed users, and wherein said words are associated with a value, a need, a goal, or any combination thereof.

7. The method as set forth in claim 1, wherein one or more of said domains comprises a romantic interaction, a transportation organization, an exercise goal, a fitness goal, a diet regimen, a smoking habit, an addiction, a cause, a community service, a physical activity, an emotional state, or any combination thereof.

8. A system for profile matching based on network behavior, said system comprising:

(a) an application server for operating a computer-implemented social network of a plurality of users;

(b) a database for storing network behaviors of at least some of said plurality of users of said social network, called observed users, wherein said network behaviors of each of said observed users comprise;

(i) a customization of a visual graphic by the same of said observed users;

(ii) a media preference of the same of said observed users; and

(iii) a communication preference of the same of said observed users;

(c) a profiling function for profiling at least some of said observed users based on said observed network behaviors of the same of said observed users, wherein said profiling is with respect to at least one or more domains, wherein said profiling function associates one or more scale factors for each of said observed network behaviors based on a relevance of the same of said observed network behaviors to said domain used in said profiling;

(d) a matching function for matching two or more of said profiled users with respect to the same of said domains, wherein said matching is based on said profiling;

(e) a rating function for rating a quality of said user matching, wherein said rating is based on one or more user inputs of said user matching, a participation data of an activity by said matched users, or any combination thereof; and

(f) an updating function for updating said profiling by refining said scale factors based on said rating.

9. The method as set forth in claim 8, wherein said visual graphic comprises an avatar, and wherein said customization comprises determining an appearance of said avatar.

10. A method of profiling users based on observed network behavior, said method comprising:

(a) providing a computer-implemented social network of a plurality of users;

(b) observing network behaviors of one of said users of said computer-implemented social network, called observed users, wherein said network behaviors of said observed user comprise;

(i) a customization of a visual graphic by said observed user;

(ii) a media preference of said observed user, wherein said media preference is associated with a media content, a media type, a frequency of media playback, or any combination thereof; and

(iii) a communication preference of said observed user, wherein said communication preference comprises a communication method, a communication timing, a communication frequency;

(c) providing a domain for user profiling, wherein said domain is related to a need of said observed user, a goal of said observed user, or any combination thereof;

(d) associating a scale factor for each of said network behaviors of said observed user, wherein said scale factors are with respect to said domain;

(e) profiling said observed user based on said associated scale factors of each of said network behaviors.

11. The method as set forth in claim 10, wherein said visual graphic comprises an avatar, and wherein said customization comprises determining an appearance of said avatar.

12. The method as set forth in claim 10, wherein one of said network behaviors comprises a selection of words from a word list by said observed user, and wherein said words are associated with values, needs, goals, or any combination thereof.