CLASSIFICATION OF DIGITAL CONTENT BY USING AGGREGATE SCORING

• US 20090177670A1
• Filed: 01/09/2008
• Published: 07/09/2009
• Est. Priority Date: 01/09/2008
• Status: Active Grant

• Current Assignee: Khoros LLC
• Original Assignee: Keibi Technologies, Inc. (Khoros LLC)
• Inventors: Grenier, Pierre, Sandhu, Satinderpal, Lo, Eddie
• Granted Patent: US 7,979,369 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

Aggregate scoring is used to help classify digital content such as content uploaded to multi-user websites (e.g., social networking websites). In one embodiment, specific categories are used that relate to a social implication of content. For example, text, images, audio or other data formats can provide communication perceived to fall into categories such as violent, abusive, rights management, pornographic or other types of communication. The categories are used to provide a raw score to items in various groupings of a site'"'"'s content. Where items are related to other items such as by organizational, social, legal, data-driven, design methods, or by other principles or definitions, the related items'"'"' raw scores are aggregated to achieve a score for a particular grouping of items that reflects, at least in part, scores from two or more of the related items.

Claims

1. A method for classifying digital content, wherein the digital content includes two or more items, the method comprising:

identifying a grouping of the two or more items in the digital content;

assigning a raw score to the identified items based on predetermined criteria;

deriving an aggregate score for the digital content, wherein the aggregate score is derived from the raw scores; and

using the aggregate score to output a classification of the digital content.

2. The method of claim 1, wherein the classification includes an indication of a level of objectionable content within the digital content.

3. The method of claim 1, wherein the classification includes an indication of a level of violent content within the digital content.

4. The method of claim 1, wherein the classification includes an indication of a level of pornographic content within the digital content.

5. The method of claim 1, wherein the classification includes an indication of a level of abusive content within the digital content.

6. The method of claim 1, wherein the classification includes an indication of a level of proprietary content within the digital content.

7. The method of claim 1, wherein an item includes text.

8. The method of claim 1, wherein an item includes an image.

9. The method of claim 1, wherein an item includes a visual presentation.

10. The method of claim 9, wherein the visual presentation includes a plurality of images.

11. The method of claim 10, wherein the plurality of images comprises a video.

12. The method of claim 10, wherein the plurality of images comprises an animation.

13. The method of claim 1, wherein the items are included in a level.

14. The method of claim 13, wherein a level includes a web page.

15. The method of claim 13, wherein a level includes a post by a user.

16. The method of claim 1, further comprising:

weighting one or more of the raw scores in order to derive the aggregate score.

17. The method of claim 1, further comprising:

wherein the aggregate score is used to derive a category score.

18. The method of claim 17, wherein the category score is derived for a web page.

19. The method of claim 17, wherein the category score is derived for a uniform resource locator (URL) address.

20. The method of claim 17, wherein the category score is derived for a user account.

21. The method of claim 17, wherein the category score is derived for a web page.

22. The method of claim 1, further comprising:

deriving one or more of the raw scores by using voting results from a user community.

23. The method of claim 1, further comprising:

deriving one or more of the raw scores by using flagging from a user community.

24. The method of claim 1, further comprising:

deriving one or more of the raw scores by using information from multiple websites.

25. An apparatus for classifying digital content, wherein the digital content includes two or more items, the apparatus comprising:

a processor;

a machine-readable storage medium including one or more instructions executable by the processor for;

identifying a grouping of the two or more items in the digital content;

assigning a raw score to the identified items based on predetermined criteria;

deriving an aggregate score for the digital content, wherein the aggregate score is derived from the raw scores; and

using the aggregate score to output a classification of the digital content.

26. A machine-readable storage medium including instructions for classifying digital content, wherein the digital content includes two or more items, the machine-readable storage medium comprising one or more instructions for:

identifying a grouping of the two or more items in the digital content;

assigning a raw score to the identified items based on predetermined criteria;

deriving an aggregate score for the digital content, wherein the aggregate score is derived from the raw scores; and

using the aggregate score to output a classification of the digital content.