System and method to facilitate matching of content to advertising information in a network

• US 8,688,521 B2
• Filed: 07/20/2007
• Issued: 04/01/2014
• Est. Priority Date: 07/20/2007
• Status: Expired due to Fees

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Broder, Andrei Zary, Fontoura, Marcus Felipe, Josifovski, Vanja, Riedel, Lance Alan
• Primary Examiner(s): LI, SUN M
• Application Number:
  US11/781,147
• Publication Number:
  US 20090024468A1
• Time in Patent Office: 2,447 Days
• Field of Search: 705 1- 20, 707 1- 10, 707/700, 707/710, 709 1- 10
• US Class Current: 705/14.71
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

A system and method to facilitate matching of content to advertising information in a network are described. A request for advertising information is received over a network, the advertising information to be displayed for a user entity in association with content information within a web page requested by the user entity. Advertising information related to one or more themes of the content information on the web page is further determined, the themes representing subject matter contextually related to the content information. Advertisements are further selected from the advertising information based on keywords and metadata stored within the web page and based on a set of predetermined parameters stored within the data storage module. The selected advertisements are further ranked to obtain a ranked list of advertisements. The ranked list of advertisements is subsequently optimized based on feedback data to obtain a list of optimized advertisements to be displayed for the user entity on the requested web page.

Claims

1. A computer-implemented method comprising:

receiving, by a processor, a request for advertising information in association with web page content information within a web page requested by a user entity;

retrieving, by a processor, a content category associated with said web page content information from a hierarchical content taxonomy based on a theme of said web page content information;

retrieving, by a processor, an advertising category associated with said advertising information from a hierarchical advertising taxonomy based on a mapping probability table that associates the content category with the advertising category,

wherein the mapping probability table comprises;

a match between the theme of the web page content information and an advertisement in the advertising category, wherein the match is based on a logical association of the content category and the advertising category and not upon the web page content information alone; and

mapping information, comprising at least one probability score corresponding to a likelihood, based on the match, that a viewer who is interested in said content category is interested in the advertising category; and

retrieving, by a processor, the advertisement to display on the user entity.

2. The computer-implemented method according to claim 1, wherein said request for advertising information is received from a user entity over a network.

3. The computer-implemented method according to claim 1, wherein said request for advertising information is received from a publisher entity over a network.

4. The computer-implemented method according to claim 1, further comprising:

selecting, by a processor, a plurality of advertisements from said advertising information based on keywords and metadata stored within said web page and a set of predetermined parameters; and

ranking, by a processor, said selected advertisements to obtain a ranked list of advertisements.

5. The computer-implemented method according to claim 4, further comprising:

extracting, by a processor, said keywords and said metadata associated with said web page; and

retrieving, by a processor, said predetermined set of parameters from at least one database.

6. The computer-implemented method according to claim 5, wherein said predetermined set of parameters further comprises at least one of user profile information related to said user entity, business rules related to processing and display of said advertisements, and financial parameters related to said selected advertisements.

7. The computer-implemented method according to claim 4, further comprising:

optimizing, by a processor, said ranked list of advertisements based on feedback data to obtain a list of optimized advertisements to be displayed for said user entity on said requested web page.

8. A computer system comprising:

at least one web server, comprising a processor and memory, the at least one web server configured to receive a request for advertising information in association with web page content information within a web page requested by a user entity; and

a processing and matching platform, comprising a processor and memory, coupled to said at least one web server, the processing and matching platform configured to;

retrieve a content category associated with said web page content information from a hierarchical content taxonomy based on a theme of said web page content information;

retrieve an advertising category associated with said advertising information from a hierarchical advertising taxonomy based on a mapping probability table that associates the content category with the advertising category,

wherein the mapping probability table comprises;

a match between the theme of the web page content information and an advertisement in the advertising category, wherein the match is based on a logical association of the content category and the advertising category and not upon the web page content information alone; and

mapping information, comprising at least one probability score corresponding to a likelihood, based on the match, that a viewer who is interested in said content category is interested in the advertising category associated with said advertising information; and

retrieve said advertisement to display on the user entity.

9. The computer system according to claim 8, wherein said request for advertising information is received from a user entity over a network.

10. The computer system according to claim 8, wherein said request for advertising information is received from a publisher entity over a network.

11. The computer system according to claim 8, wherein said platform is further configured to:

select advertisements from said advertising information based on keywords and metadata stored within said web page and a set of predetermined parameters, and

rank said selected advertisements to obtain a ranked list of advertisements.

12. The computer system according to claim 11, wherein said platform is further configured to:

extract said keywords and said metadata associated with said web page, and

retrieve said predetermined set of parameters from at least one database.

13. The computer system according to claim 12, wherein said predetermined set of parameters further comprises at least of user profile information related to said user entity, business rules related to processing and display of said advertisements, and financial parameters related to said selected advertisements.

14. The computer system according to claim 11, wherein said platform is further configured to optimize said ranked list of advertisements based on feedback data to obtain a list of optimized advertisements to be displayed on said requested web page.

15. A non-transitory computer readable storage medium containing executable instructions, which, when executed in a processing system by a processor, cause said system to perform acts of:

receiving a request for advertising information in association with web page content information within a web page requested by a user entity;

retrieving a content category associated with said web page content information from a hierarchical content taxonomy based on a theme of said web page content information;

retrieving an advertising category associated with said advertising information from a hierarchical advertising taxonomy based on a mapping probability table that associates the content category with the advertising category,

wherein the mapping probability table comprises;

a match between the theme of the web page content information and an advertisement in the advertising category, wherein the match is based on a logical association of the content category and the advertising category and not upon the web page content information alone; and

mapping information, comprising at least one probability score corresponding to a likelihood, based on the match, that a viewer who is interested in said content category is interested in the advertising category; and

retrieving the advertisement to display on the user entity.

16. The non-transitory computer readable storage medium according to claim 15, wherein said request for advertising information is requested from a user entity over a network.

17. The non-transitory computer readable storage medium according to claim 15, wherein said request for advertising information from a publisher entity over a network.

18. The non-transitory computer readable storage medium according to claim 15, wherein said executable instructions, when executed in a processing system by a processor, further cause said system to perform acts of:

selecting advertisements from said advertising information based on keywords and metadata stored within said web page and a set of predetermined parameters; and

ranking said selected advertisements to obtain a ranked list of advertisements.

19. The non-transitory computer readable storage medium according to claim 18, wherein said executable instructions, when executed in a processing system by a processor, further cause said system to perform acts of:

extracting said keywords and said metadata associated with said web page; and

retrieving said predetermined set of parameters form at least one database.

20. The non-transitory computer readable storage medium according to claim 19, wherein said predetermined set of parameters further comprises at least one of user profile information related to said user entity, business rules related to processing and display of said advertisements, and financial parameters related to said selected advertisements.

21. The non-transitory computer readable storage medium according to claim 18, wherein said executable instructions, when executed in a processing system by a processor, further cause said system to perform acts of:

optimizing said ranked list of advertisements based on feedback data to obtain a list of optimized advertisements to be displayed for said user entity on said requested web page.

22. The non-transitory computer readable storage medium according to claim 21, wherein said executable instructions, when executed in a processing system by a processor, further cause said system to perform acts of:

storing said optimized advertisements and their association with said web page and said content information within at least one database of said data storage module.