GENERATING CONTENT RECOMMENDATIONS

• US 20130332462A1
• Filed: 06/12/2012
• Published: 12/12/2013
• Est. Priority Date: 06/12/2012
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Billmaier, David Paul, Hall, Jason Christopher, Kellum, John Max, Yamamoto, Henry Hideyuki, Barclay, Alexander Charies
• Application Number:
  US13/494,320
• Publication Number:
  US 20130332462A1
• Time in Patent Office: Days
• US Class Current: 707/741
• CPC Class Codes: G06F 16/686 using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings

Abstract

A system to generate content recommendations by identifying content and selecting a content entry for the content. The system comprises identifying a keyword in the content entry, generating a tag for the content based on the keyword, generating a plurality of recommendations based on the tag, and displaying the recommendations.

Claims

1. A method for generating content recommendations comprising:

identifying content;

selecting a content entry for the content;

identifying a keyword in the content entry;

generating a tag for the content based on the keyword;

generating a plurality of recommendations based on the tag; and

displaying the recommendations.

2. The method of claim 1 further comprising:

generating a playlist of content comprising a plurality of items;

generating a plurality of tags, wherein each of the tags corresponds to an item; and

identifying a theme of the playlist of content based on the tags.

3. The method of claim 1, wherein the content comprises audio content.

4. The method of claim 3, wherein generating the recommendations based on the tag comprises identifying related audio content comprising at least one common characteristic with the content.

5. The method of claim 1, wherein identifying the keyword in the content entry comprises:

searching the content entry for a term; and

determining the term is repeated a specified number of times.

6. The method of claim 1, wherein generating the recommendations based on the tag comprises:

identifying a plurality of potential recommendations;

selecting a portion of the potential recommendations; and

identifying the portion of the potential recommendations as a set of actual recommendations.

7. The method of claim 1, comprising storing the tag for the content in the content entry.

8. The method of claim 1, wherein identifying the keyword in the content entry comprises:

determining a user preference; and

identifying the keyword based on the user preference.

9. A system comprising:

a network interface card to select a content entry from a server through a network;

a display device to display content and the content entry;

a memory device to store a recommendation application, wherein the recommendation application is to generate content recommendations; and

a processor to;

identify content;

select a content entry for the content;

detect a user preference;

identify a keyword based on the user preference;

generate a tag for the content based on the keyword;

generate a plurality of recommendations based on the tag; and

display the recommendations.

10. The system of claim 9, wherein the processor executable code also causes the processor to:

generate a playlist of content comprising a plurality of items;

generate a plurality of tags, wherein each of the tags corresponds to an item; and

identify a theme of the playlist of content based on the tags.

11. The system of claim 9, wherein the content comprises audio content.

12. The system of claim 11, wherein the processor executable code also causes the processor to identify related audio content comprising at least one common characteristic with the content.

13. The system of claim 9, wherein the processor executable code also causes the processor to:

search the content entry for a term; and

determine the term is repeated a specified number of times.

14. The system of claim 9, wherein the processor executable code also causes the processor to:

identify a plurality of potential recommendations;

select a portion of the potential recommendations; and

identify the portion of the potential recommendations as the plurality of actual recommendations.

15. A tangible, non-transitory, computer-readable medium comprising code to direct a processor to:

identify content;

select a content entry for the content;

detect a user preference;

identify a keyword based on the user preference;

generate a tag for the content based on the keyword;

generate a plurality of recommendations based on the tag; and

display the recommendations.

16. The tangible, non-transitory computer-readable medium of claim 15 comprising code to also direct a processor to:

generate a playlist of content comprising a plurality of items;

generate a plurality of tags, wherein each of the tags corresponds to an item; and

identify a theme of the playlist of content based on the tags.

17. The tangible, non-transitory computer-readable medium of claim 15, wherein the content comprises audio content.

18. The tangible, non-transitory computer-readable medium of claim 17 comprising code to also direct a processor to identify related audio content comprising at least one common characteristic with the content.

19. The tangible, non-transitory computer-readable medium of claim 15 comprising code to also direct a processor to:

search the content entry for a term; and

determine the term is repeated a specified number of times.

20. The tangible, non-transitory computer-readable medium of claim 15 comprising code to also direct a processor to:

identify a plurality of potential recommendations;

select a portion of the potential recommendations; and

identify the portion of the potential recommendations as the plurality of actual recommendations.