Determining prospective advertising hosts using data such as crawled documents and document access statistics

• US 20060095322A1
• Filed: 11/03/2004
• Published: 05/04/2006
• Est. Priority Date: 11/03/2004
• Status: Abandoned Application

• Current Assignee: Google Inc. (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Dierks, Timothy Matthew
• Application Number:
  US10/980,398
• Publication Number:
  US 20060095322A1
• Time in Patent Office: Days
• US Class Current: 705/14.46
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

Ad delivery systems want to find good advertising partners easily and efficiently. To this end, available data such as crawled Webpages, access statistics, advertising offers, etc. may be analyzed. The available Webpages may be scored and sorted based on estimated revenue of the Webpages. The scored and sorted Webpges may then be filtered to remove documents considered to be poor prospects and/or documents having characteristics that are considered to make the documents poor prospects, and then presented to the ad delivery system for further use.

Claims

1. A computer-implemented method comprising:

a) accepting documents;

b) scoring the documents to provide a score for each of the documents;

c) sorting the scored documents using the scores; and

d) filtering the documents to remove documents that are not likely to be good prospective advertising partners.

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

e) after filtering and scoring the documents, presenting the documents as prospective advertising partners.

3. The computer-implemented method of claim 1 wherein the act of scoring the documents scores each document using an estimated number of impressions of the document over a time period.

4. The computer-implemented method of claim 1 wherein the act of scoring the documents scores each document using ad information.

5. The computer-implemented method of claim 4 wherein the ad information includes information targeting one or more ads to the document.

6. The computer-implemented method of claim 4 wherein the ad information includes offer information of one or more ads targeted to the document.

7. The computer-implemented method of claim 1 wherein the act of filtering includes removing documents belonging to a predetermined set of documents.

8. The computer-implemented method of claim 1 wherein the documents are Webpages, and wherein the act of filtering includes removing Webpages belonging to a predetermined set of Webpages.

9. The computer-implemented method of claim 8 wherein the predetermined set of Webpages is a Website.

10. The computer-implemented method of claim 1 wherein the documents are Webpages, and wherein the act of filtering includes removing government Webpages.

11. The computer-implemented method of claim 1 wherein the act of filtering documents includes removing documents known to have a policy of excluding advertisements.

12. A computer-implemented method comprising:

a) accepting documents;

b) scoring the documents to provide a score for each of the documents, wherein the act of scoring the documents scores each document using ad information; and

c) sorting the scored documents using the scores.

13. The computer-implemented method of claim 12 further comprising:

d) presenting the sorted documents as prospective advertising partners.

14. The computer-implemented method of claim 12 wherein the act of scoring the documents scores each document using an estimated number of impressions of the document over a time period.

15. The computer-implemented method of claim 12 wherein the ad information includes information targeting one or more ads to the document.

16. The computer-implemented method of claim 12 wherein the ad information includes offer information of one or more ads targeted to the document.

17. The computer-implemented method of claim 12 wherein the score for each document is determined using an estimated advertising revenue of serving a set of one or more ads with an impression of the document.

18. The computer-implemented method of claim 17 wherein the score further includes an estimated number of impressions of the document over a given time period.

19. The computer-implemented method of claim 12 wherein the score for each document includes a product of (i) an estimated advertising revenue of serving a set of one or more ads with an impression of the document and (ii) an estimated number of impressions of the document over a given time period.

20. Apparatus comprising:

a) means for accepting documents;

b) means for scoring the documents to provide a score for each of the documents;

c) means for sorting the scored documents using the scores; and

d) means for filtering the documents to remove documents that are not likely to be good prospective advertising partners.

21. Apparatus comprising:

a) means for accepting documents;

b) means for scoring the documents to provide a score for each of the documents, wherein the act of scoring the documents scores each document using ad information; and

c) means for sorting the scored documents using the scores.