Blog advertising

• US 20080201222A1
• Filed: 04/25/2007
• Published: 08/21/2008
• Est. Priority Date: 02/16/2007
• Status: Active Grant

• Current Assignee: Ecairn, Inc.
• Original Assignee: Ecairn, Inc.
• Inventors: Lahaix, Dominique
• Granted Patent: US 8,527,594 B2
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0245 Surveys
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

Blog advertisement selection and placement is driven by the analysis of different facets, which are defined as why-facet, how-facet, who-facet and what-facet. The objective of defining such facets and their labels is to be able to better classify and distinguish information from blogs with the goal to use these different facets to better target advertisements on blogs. A model of features is built and maintained that classifies information from blogs along the defined facets. The features, including non-keywords and keywords, are extracted from a set of blogs of at least one blogosphere. Non-keywords are related to the blog information and keywords, and assist the keywords in the classification of the different facets/labels. An advertising campaign is defined in terms of the defined facets. The model and the defined advertising campaign will then be able to determine and/or predict placement of an advertisement in a blog or blog page.

Claims

1. A method for selecting and placing an advertisement, comprising the steps of:

(a) defining a why-facet and a how-facet, wherein said why-facet defines an objective of an advertising message and/or an advertising target, and wherein said how-facet defines a style of said advertising message and/or said advertising target;

(b) having a model of features classified along said why-facet and said how-facet, said model is based on;

(i) extracting features from a set of blogs of at least one blogosphere, wherein said features include non-keywords and keywords, and

(ii) classifying said extracted features along said why-facet and said how facet;

(c) defining an advertising campaign in terms of said defined why-facet and/or said how-facet; and

(d) using said model to determine placement of said advertisement in a blog.

2. The method as set forth in claim 1, wherein said why-facet comprises why-facet labels.

3. The method as set forth in claim 2, wherein said why-facet labels are adopt, use or improve.

4. The method as set forth in claim 1, wherein said how-facet comprises how-facet labels.

5. The method as set forth in claim 4, wherein said how-facet labels differentiate the style, originality, nature or complexity of an advertisement or a message.

6. The method as set forth in claim 1, further comprising:

(a) a defining a what-facet, wherein said what-facet comprises what-facet labels and defines the type of product or service of said advertising message and/or said advertising target;

(b) said model classifying along said what-facet; and

(c) said advertising campaign defining in terms of said defined what-facet.

7. The method as set forth in claim 1, further comprising:

(a) a defining a who-facet, wherein said who-facet comprises who-facet labels and defines the type of audience for said advertising message and/or said advertising target;

(b) said model classifying along said who-facet; and

(c) said advertising campaign defining in terms of said defined who-facet.

8. The method as set forth in claim 1, wherein said method is a computer implemented program.

9. The method as set forth in claim 1, wherein said determining is predicting using said model, wherein said blog for advertisement placement is different than said set of blogs used to in said model.

10. The method as set forth in claim 1, wherein said method does not rely on any self-declared profile, demographic description or survey.

11. A computer-readable storage medium containing a set of instructions executable on a computer, said set of instructions comprising:

(a) a definition routine for defining a why-facet and a how-facet, wherein said why-facet defines an objective of an advertising message and/or an advertising target, and wherein said how-facet defines a style of said advertising message and/or said advertising target;

(b) a model routine for having a model of features classified along said why-facet and said how-facet, said model is based on;

(i) extracting features from a set of blogs of at least one blogosphere, wherein said features include non-keywords and keywords, and

(ii) classifying said extracted features along said why-facet and said how facet;

(c) an advertisement campaign definition routine for defining an advertising campaign in terms of said defined why-facet and/or said how-facet; and

(d) an advertisement placement routine that uses said model to determine placement of said advertisement in a blog.

12. The computer-readable storage medium as set forth in claim 11, wherein said why-facet comprises why-facet labels.

13. The computer-readable storage medium as set forth in claim 12, wherein said why-facet labels are adopt, use or improve.

14. The computer-readable storage medium as set forth in claim 11, wherein said how-facet comprises how-facet labels.

15. The computer-readable storage medium as set forth in claim 14, wherein said how-facet labels differentiate the style, originality, nature or complexity of an advertisement or a message.

16. The computer-readable storage medium as set forth in claim 12, wherein:

(a) said definition routine further comprises defining a what-facet, wherein said what-facet comprises what-facet labels and defines the type of product or service of said advertising message and/or said advertising target;

(b) said model routine further comprises classifying said model along said what-facet; and

(c) said advertisement campaign definition routine further comprises defining said advertising campaign routine in terms of said defined what-facet.

17. The computer-readable storage medium as set forth in claim 11, wherein:

(a) said definition routine further comprises defining a who-facet, wherein said who-facet comprises who-facet labels and defines the type of audience for said advertising message and/or said advertising target;

(b) said model routine further comprises classifying said model along said who-facet; and

(c) said advertisement campaign definition routine further comprises defining said advertising campaign routine in terms of said defined who-facet.

18. The computer-readable storage medium as set forth in claim 11, wherein said determining is predicting using said model, wherein said blog for advertisement placement is different than said set of blogs used to in said model.

19. The computer-readable storage medium as set forth in claim 11, wherein said advertisement campaign definition routine does not rely on any self-declared profile, demographic description or survey.

20. The computer-readable storage medium as set forth in claim 11, wherein said advertisement placement routine comprises a prediction routine to predict the advertisement placement, wherein said blog for advertisement placement is different than said set of blogs used to in said reference model.