System and method for user classification based on social network aware content analysis

• US 8,135,800 B1
• Filed: 12/27/2006
• Issued: 03/13/2012
• Est. Priority Date: 12/27/2006
• Status: Expired due to Fees

• Current Assignee: Qurio Holdings Incorporated
• Original Assignee: Qurio Holdings Incorporated
• Inventors: Walsh, Richard, Amidon, Christopher, Issa, Alfredo
• Primary Examiner(s): Nguyen, Phuoc
• Assistant Examiner(s): Belani, Kishin G
• Application Number:
  US11/645,864
• Time in Patent Office: 1,903 Days
• Field of Search: 709/217, 709/201, 707/723
• US Class Current: 709/217
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification

Abstract

A target user'"'"'s profile may be generated based on scanning metadata related to various content items made available for sharing by the user. For instance, some content items may be made available for sharing by the target user while other items are made available for sharing by one or more other users in the target user'"'"'s social network. A list of keywords related to each item may be generated from the metadata. Each keyword may then be scored using social network data. For example, social network data corresponding to one or more users associated with each content item may be used to score keywords related to that item. Scoring may be based on factors such as social network distance, relationship type, trust, length of time in the social network, amount of content, amount of metadata, and other factors.

Claims

1. A non-transitory computer-readable medium comprising computer instructions embodied therein, wherein the computer instructions, when executed by at least one computing device, configure the at least one computing device to perform actions comprising:

selecting a user from a plurality of users in a social network of a target user;

scanning metadata associated with content items shared by the selected user;

determining a list of keywords associated with the content items based on the metadata;

accessing social network data associated with the selected user, the social network data including a relationship classifier that classifies a relationship between the selected user and the target user and a social network distance between the target user and the selected user, and a trust classifier that classifies a trust level between the selected user and the target user;

determining a plurality of keyword scores based on the social network data, each of the plurality of keyword scores corresponding to one of the keywords on the list of keywords, wherein each of the plurality of scores is weighted by the trust classifier and an adjustment factor inversely proportional to the social network distance;

normalizing individual keyword scores of the plurality of keywords scores based on a number of the content items shared by the selected user in comparison to a number of content items shared by other selected users of the plurality of users when the number of the content items shared by the selected user is greater than the number of content items shared by other selected users of the plurality of users; and

generating a profile for the target user, the profile having the list of keywords and the corresponding plurality of keyword scores based on the scoring of each keyword.

2. The non-transitory computer-readable medium as set forth in claim 1, wherein scanning the metadata associated with the content items includes interfacing with at least one content sharing computing device and obtaining content metadata related to the content items.

3. The non-transitory computer-readable medium as set forth in claim 1, wherein accessing the social network data includes interfacing with at least one social network computing device and obtaining the social network data associated with the selected user.

4. The non-transitory computer-readable medium as set forth in claim 1, wherein determining the plurality of keyword scores includes determining a length of time the selected user has participated in the social network of the target user.

5. The non-transitory computer-readable medium as set forth in claim 1, wherein determining the plurality of keyword scores includes determining a type characterizing the relationship between the target user and the selected user.

6. The non-transitory computer-readable medium as set forth in claim 1, wherein determining the plurality of keyword scores includes accessing data characterizing the trust level between the target user and the selected user.

7. The non-transitory computer-readable medium as set forth in claim 1, wherein determining the plurality of keyword scores includes accessing data indicating a location of the selected user.

8. The non-transitory computer-readable medium as set forth in claim 1, wherein the computer instructions configure the at least one computing device to perform actions including:

for each content item associated with each selected user, determining access rights of the target user to each content item;

wherein generating the list of keywords is based at least in part on the access rights of the target user to each content item; and

wherein no keywords are generated for any content items the target user cannot access.

9. The non-transitory computer-readable medium as set forth in claim 1, wherein the computer instructions configure the at least one computing device to perform actions further including:

prior to scanning the metadata associated with the content items, first determining whether to access the metadata based on one or more access parameters.

10. The non-transitory computer-readable medium as set forth in claim 9, wherein at least one of the access parameters is a privacy setting.

11. The non-transitory computer-readable medium as set forth in claim 1, wherein the computer instructions configure the at least one computing device to perform actions further including:

for each selected user, normalizing a contribution of points from the selected user to the target user'"'"'s profile.

12. The non-transitory computer-readable medium as set forth in claim 11, wherein normalizing includes accessing data stored in a points allocation profile.

13. A computer-implemented method of profiling a target user having a social network including a plurality of users, the method comprising:

selecting a user from the plurality of users in the social network of the target user;

scanning metadata associated with content items shared by the selected user;

determining a list of keywords associated with the content items based on the metadata;

accessing social network data associated with the selected user, the social network data including a relationship classifier that classifies a relationship between the selected user and the target user and a social network distance between the target user and the selected user, and a trust classifier that classifies a trust level between the selected user and the target user;

determining a plurality of keyword scores based on the social network data, each of the plurality of keyword scores corresponding to one of the keywords on the list of keywords, wherein each of the plurality of scores is weighted by the trust classifier and an adjustment factor inversely proportional to the social network distance;

normalizing individual keyword scores of the plurality of keywords scores based on a number of the content items shared by the selected user in comparison to a number of content items shared by other selected users of the plurality of users when the number of the content items shared by the selected user is greater than the number of content items shared by other selected users of the plurality of users; and

generating a profile for the target user, the profile having the list of keywords and the corresponding plurality of keyword scores based on the scoring of each keyword.

14. The computer-implemented method as set forth in claim 13, wherein scanning the metadata associated with the content items includes interfacing with at least one content sharing computing device and obtaining content metadata related to the content items.

15. The computer-implemented method as set forth in claim 13, wherein accessing the social network data includes interfacing with at least one social network computing device and obtaining the social network data associated with the selected user.

16. The computer-implemented method as set forth in claim 13, wherein determining the plurality of keyword scores includes determining a length of time the selected user has participated in the social network of the target user.

17. The computer-implemented method as set forth in claim 13, wherein determining the plurality of keyword scores includes determining a type characterizing the relationship between the target user and the selected user.

18. The computer-implemented method as set forth in claim 13, wherein determining the plurality of keyword scores includes accessing data characterizing the trust level between the target user and the selected user.

19. The computer-implemented method as set forth in claim 13, wherein determining the plurality of keyword scores includes accessing data indicating a location of the selected user.

20. The computer-implemented method as set forth in claim 13, further comprising:

determining access rights of the target user to each content item associated with each selected user;

wherein generating the list of keywords is based at least in part on the access rights of the target user to the content item; and

wherein no keywords are generated for any content items that the target user cannot access.

21. The computer-implemented method as set forth in claim 13, further comprising:

prior to scanning the metadata associated with the content items, determining whether to access the metadata based on one or more access parameters.

22. The computer-implemented method as set forth in claim 21, wherein at least one access parameter is a privacy setting.

23. The computer-implemented method as set forth in claim 13, further comprising:

for each selected user, normalizing a contribution of points of the selected user to the target user'"'"'s profile.

24. The computer-implemented method as set forth in claim 23, wherein normalizing includes accessing data stored in a points allocation profile.