System and Method for Targeted Advertisements for Video Content Delivery

• US 20110185384A1
• Filed: 12/01/2010
• Published: 07/28/2011
• Est. Priority Date: 01/28/2010
• Status: Abandoned Application

• Current Assignee: Futurewei Technologies Incorporated (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Futurewei Technologies Incorporated (Huawei Investment & Holding Co., Ltd.)
• Inventors: Wang, Shu, Wang, Qi, Huang, Yu, Zhang, Dong-Qing, Yu, Hong Heather
• Application Number:
  US12/958,072
• Publication Number:
  US 20110185384A1
• Time in Patent Office: Days
• US Class Current: 725/34
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: H04N 21/23424 involving splicing one content stream with another content stream, e.g. for inserting or substituting an advertisement
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/4756 for rating content, e.g. scoring a recommended movie
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38
• CPC Class Codes: H04N 21/84 Generation or processing of descriptive data, e.g. content descriptors systems specially adapted for using meta-information in broadcast systems H04H60/73
• CPC Class Codes: H04N 21/8456 by decomposing the content in the time domain, e.g. in time segments

Abstract

In accordance with an embodiment, a method of inserting advertisements into video content includes electronically receiving video content metadata from a content provider, matching the video content metadata to advertising content metadata to provide a first list of advertisements, filtering the first list of advertisements according to user preference data to determine a second list of advertisements, and transmitting the second list of advertisements to a user device for insertion into the video content. The video content metadata corresponds to video content being sent to a user device, and the advertising content metadata corresponds to advertising content.

Claims

1. A method of inserting advertisements into video content, the method comprising:

electronically receiving video content metadata from a content provider, the video content metadata corresponding to video content being sent to a user device;

matching the video content metadata to advertising content metadata to provide a first list of advertisements, the advertising content metadata corresponding to advertising content;

filtering the first list of advertisements according to user preference data to determine a second list of advertisements; and

transmitting the second list of advertisements to a user device for insertion into the video content.

2. The method of claim 1, wherein:

the video content comprises a plurality of video segments;

each video segment is associated with video content metadata; and

matching the video content metadata and filtering the first list of advertisements is performed on a segment by segment basis.

3. The method of claim 1, further comprising receiving user preference data from the user device.

4. The method of claim 1, wherein:

the video content metadata comprises at least one keyword;

the advertising content metadata comprises at least one keyword; and

matching the video content metadata to the advertising content metadata comprises comparing the at least one keyword of the video content metadata to the at least one keyword of the advertising content metadata.

5. The method of claim 4, wherein matching the video content metadata to advertising content metadata comprises:

incrementing a match metric based on the comparing;

comparing the incremented match to a predetermined threshold; and

if the incremented match exceeds the predetermined threshold, add the advertising content to the first list of advertisements.

6. The method of claim 4, wherein:

the video content metadata comprises a video category; and

the advertising content metadata comprises an advertisement category.

7. The method of claim 6, wherein the video category and the advertisement category each comprise one of a group of ontological categories.

8. The method of claim 4, wherein matching the video content metadata to advertising content metadata further comprises using a lexical database to match keywords.

9. The method of claim 4, wherein

the video content metadata further comprises a first synopsis comprising a written description of the video content;

the advertising content metadata further comprises a second synopsis comprising a written description of the advertising content; and

matching the video content metadata to advertising content metadata further comprises comparing words of the first synopsis with words of the second synopsis, comparing comprising using a lexical database to match similar words.

10. The method of claim 4, wherein

the video content metadata further comprises a first category relating to the video content;

the advertising content metadata further comprises a second category relating to the advertising content; and

matching the video content metadata to advertising content metadata further comprises comparing the first category to the second category.

11. The method of claim 1, wherein:

the video content metadata further comprises a video category from a plurality of video categories relating to the video content;

the advertising content metadata further comprises an advertising category from a plurality of advertising categories relating to the advertising content; and

the user preference data comprises preference values according to the plurality of advertising categories.

12. The method of claim 11, wherein filtering the first list of advertisements comprises using a Bayesian engine.

13. The method of claim 11, wherein the plurality of advertising categories and the plurality of video categories comprise ontological categories.

14. The method of claim 11, wherein filtering the list of advertisements comprises:

selecting data from a user preference matrix;

calculating a weights according to a user profile matrix, the user profile matrix comprising further preference values according to the plurality of advertising categories;

applying the weights to the selected data in the user preference matrix to produce weighted selected data; and

calculating preference values from the weighted selected data.

15. The method of claim 14, wherein the weight values and the preference values are between −

1 and 1.

16. The method of claim 14, further comprising:

ranking preference values according to advertising categories;

determining a list of high ranking preference values; and

selecting advertisements from the first list of advertisements corresponding to high ranking preference values.

17. The method of claim 16, wherein determining the list of high ranking preference values comprises finding a highest preference value.

18. The method of claim 1, further comprising:

receiving user feedback info from the user device; and

adjusting the user preference data based on the user feedback.

19. A system for inserting advertisements into video content, the system comprising:

a metadata matching block configured to match video content metadata to advertising content metadata to provide a first list of advertisements, the advertising content metadata corresponding to advertising content, and the video content metadata corresponding to video content to be sent to a user device; and

a filtering block configured to filter the first list of advertisements according to user preference data to determine a second list of advertisements.

20. The system of claim 19, further comprising a communications adaptor configured to:

receive the video content metadata from a content provider; and

transmit the second list of advertisements to a user device for insertion into the video content.

21. The system of claim 20, wherein the communications adaptor is further configured to receive the user preference data from the user device.

22. The system of claim 19, wherein the metadata matching block is further configured to compare at least one keyword of the video content metadata to at least one keyword of the advertising content metadata.

23. The system of claim 19, wherein:

the video content metadata further comprises a video category from a plurality of video categories relating to the video content;

the advertising content metadata further comprises an advertising category from a plurality of advertising categories relating to the advertising content; and

the user preference data comprises preference values according to the plurality of advertising categories.

24. The system of claim 23, wherein the filtering block comprises a Baysian engine configured to filter the first list of advertisements.

25. The system of claim 23, wherein the filtering block is configured to:

select data from a user preference matrix;

calculate weights according to a user profile matrix, the user profile matrix comprising further preference values according to the plurality of advertising categories;

apply the weights to the selected data in the user preference matrix to produce weighted selected data; and

calculate preference values from the weighted selected data.

26. A non-transitory computer readable medium with an executable program stored thereon, wherein the program instructs a microprocessor to perform the following steps:

matching video content metadata to advertising content metadata to provide a first list of advertisements, the advertising content metadata corresponding to advertising content, and the video content metadata corresponding to video content to be sent to a user device; and

filtering the first list of advertisements according to user preference data to determine a second list of advertisements.

27. The non-transitory computer readable medium of claim 26, wherein the program further instructs the microprocessor to perform a steps of:

receiving the video content metadata from a content provider;

receiving user preference data from the user device; and

transmitting the second list of advertisements to a user device for insertion into the video content.

28. The non-transitory computer readable medium of claim 26, wherein the step of matching video content metadata further comprises comparing at least one keyword of the video content metadata to at least one keyword of the advertising content metadata.

29. The non-transitory computer readable medium of claim 26, the step of filtering the first list of advertisements comprises:

selecting data from a user preference matrix;

calculating weights according to a user profile matrix, the user profile matrix comprising preference values according to a plurality of advertising categories;

applying the weights to the selected data in the user preference matrix to produce weighted selected data; and

calculating preference values from the weighted selected data.

30. The non-transitory computer readable medium of claim 26, wherein the step of filtering the first list of advertisements comprises applying a Bayesian engine algorithm.