PREDICTING SELECTION RATES OF A DOCUMENT USING CLICK-BASED TRANSLATION DICTIONARIES

• US 20100017262A1
• Filed: 07/18/2008
• Published: 01/21/2010
• Est. Priority Date: 07/18/2008
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Raghavan, Hema, Iyer, Rukmini
• Application Number:
  US12/176,264
• Publication Number:
  US 20100017262A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

The subject matter disclosed herein relates to predicting selection rates of web-based documents in response to a search query.

Claims

1. A method comprising:

obtaining click-through information from one or more web-based search engines; and

predicting a selection of a document identified by a search query response based at least in part on a phrase/word association model based, at least in part, on said click-through information obtained from one or more previous web searches.

2. The method of claim 1, wherein said click-through information includes one or more translation tables that associate a first previous document with a second previous document.

3. The method of claim 2, further comprising building said translation tables from said previous web searches.

4. The method of claim 3, wherein a result of said previous web searches includes a selection of said first previous document in response to a display of said second previous document.

5. The method of claim 4, wherein said first previous document comprises a search query and said second previous document comprises a search result based, at least in part, on said search query.

6. The method of claim 5, wherein said second previous document comprises an advertisement.

7. The method of claim 5, wherein said search query comprises a phrase comprising two or more words.

8. The method of claim 7, further comprising:

parsing said phrase into said two or more words; and

predicting a selection of each of said two or more words using said phrase/word association model.

9. The method of claim 2, wherein said one or more translation tables include information to predict a probability that said document will be selected based, at least in part, on said first previous document and said second previous document.

10. The method of claim 1, further comprising:

predicting a selection rate of an advertisement using said phrase/word association model; and

changing said advertisement in response to said selection rate.

11. The method of claim 10, further comprising:

determining a fee to an advertiser of said advertisement in response to said selection rate.

12. An article comprising a storage medium comprising machine-readable instructions stored thereon which, if executed by a computing platform, are adapted to enable said computing platform to:

obtain click-through information from one or more web-based search engines; and

predict a selection of a document identified by a search query response based at least in part on a phrase/word association model based, at least in part, on said click-through information obtained from one or more previous web searches.

13. The method of claim 12, wherein said click-through information includes one or more translation tables that associate a first previous document with a second previous document.

14. The method of claim 13, wherein said one or more translation tables include information to predict a probability that said document will be selected based, at least in part, on said first previous document and said second previous document.

15. The method of claim 12, wherein said machine-readable instructions, if executed by a computing platform, are further adapted to enable said computing platform to:

predict a selection rate of an advertisement using said phrase/word association model; and

change said advertisement in response to said selection rate.

16. The method of claim 15, wherein said machine-readable instructions, if executed by a computing platform, are further adapted to enable said computing platform to:

determine a fee to an advertiser of said advertisement in response to said selection rate.

17. An apparatus comprising:

means for obtaining click-through information from one or more web-based search engines; and

means for predicting a selection of a document identified by a search query response based at least in part on a phrase/word association model based, at least in part, on said click-through information obtained from one or more previous web searches.

18. The apparatus of claim 17, wherein said click-through information includes one or more translation tables that associate a first previous document with a second previous document.

19. The apparatus of claim 17, further comprising:

means for predicting a selection rate of an advertisement using said phrase/word association model; and

means for changing said advertisement in response to said selection rate.

20. The apparatus of claim 19, further comprising:

means for determining a fee to an advertiser of said advertisement in response to said selection rate.