Associating Advertisements with On-Demand Media Content

• US 20080046917A1
• Filed: 07/31/2006
• Published: 02/21/2008
• Est. Priority Date: 07/31/2006
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: de Heer, David L.
• Application Number:
  US11/461,254
• Publication Number:
  US 20080046917A1
• Time in Patent Office: Days
• US Class Current: 725/32
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04N 21/23109 by placing content in organized collections, e.g. EPG data repository details of retrieval of video data and associated meta data in video databases G06F16/739
• CPC Class Codes: H04N 21/2547 Third Party Billing, e.g. billing of advertiser
• CPC Class Codes: H04N 21/4722 for requesting additional data associated with the content
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 21/858 Linking data to content, e.g. by linking an URL to a video object, by creating a hotspot
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

associating advertisements with on-demand media content is described. Advertisements are associated with media content that is available on-demand based on any number and combination of data analyses. Advertisements may be matched to media assets based on, for example, media quality, duration, time sensitivity of advertisements, positive keywords associations, and/or negative keyword associations. Auction-style bid values may also be associated with particular advertisements, such that an advertiser may be willing to pay a higher amount for the advertisement to be associated with a media asset having a particular keyword association or for the advertisement to have a more desirable placement within a play list.

Claims

1. A method, implemented at least in part by a computer, comprising dynamically associating an advertisement with an on-demand media entity based, at least in part, on a comparison of a duration associated with the advertisement and a duration associated with the on-demand media entity.

2. The method as recited in claim 1, wherein the on-demand media entity comprises at least one of a video file, a music file, a movie, a television program, a still image, an image slideshow, a collection of images, a collection of videos, a music video, a song, an album, a collection of songs, a video game, or an audio book.

3. The method as recited in claim 1, further comprising, dynamically associating the advertisement with the on-demand media entity based, at least in part, on a comparison of a media quality associated with the advertisement and a media quality associated with the on-demand media entity.

4. The method as recited in claim 3, wherein the media quality comprises a video resolution.

5. The method as recited in claim 3, wherein the media quality comprises an audio quality.

6. The method as recited in claim 1, further comprising, dynamically associating the advertisement with the on-demand media entity based, at least in part, on a comparison of a current date and time and time sensitivity data associated with the advertisement.

7. The method as recited in claim 1, further comprising, dynamically associating the advertisement with the on-demand media entity based, at least in part, on an auction bid associated with the advertisement, wherein the auction bid indicates a maximum amount an advertiser is willing to pay to have the advertisement associated with the on-demand media entity.

8. The method as recited in claim 1, further comprising, dynamically associating the advertisement with the on-demand media entity based, at least in part on a comparison of keywords associated with the advertisement and keywords associated with the on-demand media entity.

9. The method as recited in claim 8, where the keywords associated with the on-demand media entity comprise keywords extracted from closed captioning data associated with the on-demand media entity.

10. The method as recited in claim 8, where the keywords associated with the on-demand media entity comprise at least one of a title, an actor name, a rating, or song lyrics.

11. The method as recited in claim 8, where the keywords associated with the advertisement indicate keywords that may be associated with an on-demand media entity with which the advertisement may be associated.

12. The method as recited in claim 8, where the keywords associated with the advertisement indicate keywords that may be associated with an on-demand media entity with which the advertisement is not to be associated.

13. The method as recited in claim 1, further comprising:

receiving a user-request for the on-demand media entity; and

in response to the user-request, returning a play list that includes a representation of the on-demand media entity and the advertisement, such that when the on-demand media entity is played, the advertisement is also played.

14. The method as recited in claim 13, wherein, placement of the advertisement in relation to the on-demand media entity or other advertisements within the play list is based, at least in part, on a bid value associated with the advertisement.

15. A system comprising:

means for maintaining a plurality of media assets that are available on-demand;

means for maintaining a plurality of advertisements that may be associated with the media assets; and

means for dynamically associating a particular one of the plurality of advertisements with a particular one of the plurality of media assets based at least in part on a comparison of a media quality associated with the particular one of the plurality of advertisements and a media quality associated with the particular one of the plurality of media assets.

16. The system as recited in claim 15, further comprising means for dynamically associating a particular one of the plurality of advertisements with a particular one of the plurality of media assets based at least in part on a comparison of a duration associated with the particular one of the plurality of advertisements and a duration associated with the particular one of the plurality of media assets.

17. The system as recited in claim 15, further comprising means for dynamically associating a particular one of the plurality of advertisements with a particular one of the plurality of media assets based at least in part on a comparison of a keyword associated with the particular one of the plurality of advertisements and a keyword associated with the particular one of the plurality of media assets.

18. The system as recited in claim 15, further comprising:

means for maintaining bid values associated with the advertisements; and

means for dynamically associating a particular one of the plurality of advertisements with a particular one of the plurality of media assets based at least in part on a bid value associated with the particular one of the plurality of advertisements.

19. One or more computer-readable media comprising computer-executable instruction that, when executed, cause a computing system to:

associate keywords with individual ones of a plurality of on-demand media assets;

associate keywords and respective bid values with individual ones of a plurality of advertisements; and

dynamically associate a particular one of the plurality of advertisements with a particular one of the plurality of on-demand media assets based, at least in part, on;

a match between a keyword associated with the on-demand media asset and a keyword associated with the advertisement; and

an analysis of the bid value associated with the keyword and the advertisement.

20. The one or more computer-readable media as recited in claim 19, further comprising computer-executable instruction that, when executed, cause the computing system to:

associate negative keywords with individual ones of the plurality of advertisements; and

disassociate a particular one of the plurality of advertisements from a particular one of the plurality of on-demand media assets based, at least in part, on a match between a keyword associated with the on-demand media asset and a negative keyword associated with the advertisement.