Automatically generating ads and ad-serving index

• US 20070239530A1
• Filed: 03/30/2006
• Published: 10/11/2007
• Est. Priority Date: 03/30/2006
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Datar, Mayur, Garg, Ashutosh
• Granted Patent: US 8,326,686 B2
• Time in Patent Office: Days
• US Class Current: 705/14.410
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: G06Q 30/0276 Advertisement creation

Abstract

Advertiser repository information (e.g., a list of HTML pages) may be used to automatically generate a page-ad and associated ad information for each page using a subset of features of the page. Subsequently, a page-ad index for all pages from different advertisers may be created. After creating a page-ad index, if a client issues a query (e.g., from a search engine), candidate page-ads may be selected using the page-ads index. If necessary (e.g., if there are more candidate page-ads than requested ads), the candidate page-ads may be entered into an arbitration (e.g., auction). Then, the arbitration may determine a set of one or more winning page-ads to be served for rendering.

Claims

1. A computer-implemented method comprising:

a) accepting information from advertiser documents;

b) generating ads, each ad including

i) a creative, and

ii) offer information,

using the accepted information; and

d) generating an index mapping information extracted from the advertiser documents to one of (A) advertiser document identifiers for advertiser documents on which such information is found, and (B) ad identifiers for ads generated from advertiser documents on which such information is found.

2. The computer-implemented method of claim 1 wherein the advertiser documents are product Web pages.

3. The computer-implemented method of claim 1 wherein the advertiser documents are product Web pages of an e-commerce Website.

4. The computer-implemented method of claim 1 wherein the advertiser documents are services Web pages.

5. The computer-implemented method of claim 1 wherein the offer information is one of (A) an offer per ad impression, (B) a maximum offer per ad impression, (C) an offer per ad selection, (D) a maximum offer per ad selection, (E) an offer per ad conversion and (F) a maximum offer per ad conversion.

6. The computer-implemented method of claim 1 wherein the offer information is expressed in terms of a set currency.

7. The computer-implemented method of claim 1 wherein the offer information is expressed formulaically, and wherein the formula includes a product price extracted from the advertiser documents.

8. The computer-implemented method of claim 1 wherein the advertiser documents include unique addresses,

wherein each of the generated ads is associated with a specified landing page to be loaded upon ad selection, and

wherein the specified landing page is set to the unique address of the advertiser document from which the ad was generated.

9. The computer-implemented method of claim 1 wherein the advertiser documents are Web pages, each including a URL address,

wherein each ad further includes a specified landing page to be loaded upon ad selection, and

wherein the specified landing page is set to the URL address of the Web page from which the ad was generated.

10. The computer-implemented method of claim 1 wherein each of the ad creatives is generated using accepted text from the advertiser documents by selecting only some of the accepted text using at least one of (A) font size, (B) font attributes, and (C) Meta information.

11. The computer-implemented method of claim 1 wherein, in the second index, the one of (A) advertiser document identifiers for advertiser documents on which such information is found, and (B) ad identifiers for ads generated from advertiser documents on which such information is found, includes weights.

12. The computer-implemented method of claim 11 wherein the information from the advertiser documents includes terms,

wherein the second index maps terms extracted from the advertiser documents back to one of (A) advertiser document identifiers for advertiser documents on which such terms are found, and (B) ad identifiers for ads generated from advertiser documents on which such terms are found, and

wherein the weights are determined as a function of at least one of (A) font size, (B) font attributes, and (C) Meta information, of the terms in the advertiser document.

13. The computer-implemented method of claim 1 wherein the advertiser documents are product Web pages of an e-commerce Website, which Web pages are arranged in a hierarchy defined by product categories.

14. The computer-implemented method of claim 13 wherein at least some of the information for a particular product Web page is inherited from an ancestor Web page.

15. The computer-implemented method of claim 13 wherein offer information for an ad associated with a particular product Web page is inherited from an ancestor Web page.

16. The computer-implemented method of claim 1 wherein the information from the advertiser documents includes terms,

wherein the second index maps the terms extracted from the advertiser documents back to one of (A) advertiser document identifiers for advertiser documents on which such terms are found, and (B) ad identifiers for ads generated from advertiser documents on which such terms are found such that the terms are used as targeting keywords,

wherein the advertiser documents are product Web pages of an e-commerce Website, which Web pages are arranged in a hierarchy defined by product categories, and

wherein at least one of the terms is inherited from an ancestor Web page.

17. The computer-implemented method of claim 1 further comprising:

d) accepting search query information; and

e) finding one or more relevant ads using the second index and the search query information.

18. The computer-implemented method of claim 17 wherein the act of finding one or more relevant ads using the second index and the search query information includes using terms of the search query to lookup at least one of (A) advertiser document identifiers for advertiser documents on which such terms are found, and (B) ad identifiers for ads generated from advertiser documents on which such terms are found.

19. The computer-implemented method of claim 17 further comprising:

f) determining a set of one or more ads using the found one or more relevant ads as candidate ads.

20. The computer-implemented method of claim 19 wherein the act of determining a set of one or more ads using the found one or more relevant ads as candidate ads includes

scoring the candidate ads, and

accepting a subset of the candidate ads based on their scores.

21. The computer-implemented method of claim 20 wherein the act of scoring candidate ads uses offer information associated with the ads.

22. The computer-implemented method of claim 20 wherein the act of scoring candidate ads uses performance information associated with the ads.

23. The computer-implemented method of claim 20 wherein the act of scoring candidate ads uses a degree of relevance associated with the ads.

24. The computer-implemented method of claim 20 wherein the act of scoring candidate ads uses information on other pages in the hierarchy of the page for which this ad was created.

25. The computer-implemented method of claim 1 further comprising:

d) accepting document relevance information; and

e) finding one or more relevant ads using the index and the document relevance information.

26. The computer-implemented method of claim 1 wherein the offer information is expressed procedurally.

27. The computer-implemented method of claim 1 wherein the offer information is expressed procedurally using JavaScript.

28. The computer-implemented method of claim 1 further comprising:

d) generating another index mapping one of (A) advertiser document identifiers and (B) ad identifiers for ads generated from the advertiser document information, to information extracted from the advertiser documents.

29. Apparatus comprising:

a) means for accepting information from advertiser documents;

b) means for generating ads, each ad including

i) a creative, and

ii) offer information,

using the accepted information; and

c) means for generating an index mapping information extracted from the advertiser documents to one of (A) advertiser document identifiers for advertiser documents on which such information is found, and (B) ad identifiers for ads generated from advertiser documents on which such information is found.

30. A machine-readable medium having stored thereon:

an index mapping information extracted from the advertiser documents to one of (A) advertiser document identifiers for advertiser documents on which such information is found, and (B) ad identifiers for ads generated from advertiser documents on which such information is found.

31. The machine-readable medium of claim 30 further having stored thereon:

another index mapping one of (A) advertiser document identifiers and (B) ad identifiers for ads generated from the advertiser document information, to information extracted from the advertiser documents.