COMPUTERIZED SYSTEMS AND METHODS RELATED TO CONTROLLED CONTENT OPTIMIZATION

• US 20150088665A1
• Filed: 09/26/2014
• Published: 03/26/2015
• Est. Priority Date: 09/26/2013
• Status: Active Application

• Current Assignee: Yahoo AD Tech LLC
• Original Assignee: AOL Advertising Incorporated (Apollo Global Management, Inc.)
• Inventors: KARLSSON, Niklas
• Application Number:
  US14/498,494
• Publication Number:
  US 20150088665A1
• Time in Patent Office: Days
• US Class Current: 705/14.71
• CPC Class Codes: G06Q 30/0275 Auctions

Abstract

Systems, methods, and computer-readable media are disclosed for controlling the display of digital content to users over an electronic network, such as the Internet. In accordance with one implementation, a computer-implemented method is provided that includes receiving at least one partition and at least one associated candidate promotion and receiving control data and previous engagement data associated with the at least one partition. The method further comprises, for each partition, generating an adjusted model of the control data over a first time period, generating a bid price control adjustment value and a bid price value associated with an earlier time period, and generating a bid uncertainty control adjustment value and a bid uncertainty value associated with an earlier time period. The method further comprises generating a bid price and a bid uncertainty for each candidate promotion, performing a market clearing process using at least one candidate promotion, and serving at least one of the candidate promotions.

Claims

1. A computerized method for control, the method being implemented with at least one electronic processor and comprising:

receiving at least one candidate promotion and at least one partition, at least one of the candidate promotions associated with at least one partition;

receiving control data and engagement data associated with the at least one partition, the previous engagement data associated with an earlier time period;

for each partition;

generating an adjusted model of the control data over a first time period, based on data representing a traffic pattern;

generating a bid price control adjustment value based on the adjusted model and a bid price value associated with the earlier time period;

generating a bid uncertainty control adjustment value based on the adjusted model and a bid uncertainty value associated with the earlier time period;

generating a bid price and a bid uncertainty for each candidate promotion;

for each open promotion slot, performing a market clearing process using at least one candidate promotion, using a bid price and a bid uncertainty associated with each candidate promotion; and

serving at least one of the candidate promotions based on the results of the market clearing process.

2. The method of claim 1, wherein generating a bid price and a bid uncertainty for each candidate promotion comprises:

generating a probabilistic model estimating engagement data associated with the candidate promotion, the probabilistic model associated with an expected value and an expected variance;

generating the bid price, based on the expected value and the bid price control adjustment value; and

generating the bid uncertainty value, based on the expected variance and the bid uncertainty control adjustment value.

3. The method of claim 1, wherein the market clearing process comprises:

determining that at least one candidate promotion is bidding for an impression;

for each candidate promotion bidding for the impression;

generating, based on the associated bid price value and the associated bid price control adjustment value, a nominal bid price;

generating, based on the associated bid uncertainty value and the associated bid uncertainty control adjustment value, a nominal bid uncertainty;

generating a final bid for the candidate promotion using the nominal bid price and the nominal bid uncertainty;

identifying the highest bid of the final bids;

determining if a bid allocation value associated with the candidate promotion is greater than a generated random value; and

if so, outputting the candidate promotion corresponding to the highest bid.

4. The method of claim 1, wherein:

each partition is associated with a plant gain factor (K_p)and a controller gain factor (K_c(k)), where K_p and K_c(k) are related to one another in an inverse relationship; and

generating the bid uncertainty control adjustment value is further based on the controller gain factor K_c(k).

5. The method of claim 1, wherein the control data comprises data on a desired number of engagements for content promotions associated with a partition.

6. The method of claim 1, further comprising generating a factor based on the adjusted model and the previous engagement data, and wherein generating a bid price control adjustment value is based on the generated factor.

7. The method of claim 1, wherein:

the market clearing process is performed in response to a user requesting a web page, the web page containing at least one promotion slot, and

wherein serving the at least one candidate promotion comprises inserting the at least one candidate promotion into the at least one promotion slot on the web page.

8. A tangible computer-readable storage medium containing instructions that, when executed by at least one electronic processor, causes the at least one electronic processor to perform the following operations:

receiving at least one candidate promotion and at least one partition, at least one of the candidate promotions associated with at least one partition;

receiving control data and previous engagement data associated with the at least one partition, the previous engagement data associated with an earlier time period;

for each partition;

generating an adjusted model of the control data over a first time period, based on data representing a traffic pattern;

generating a bid price control adjustment value based on the adjusted model and a bid price value associated with the earlier time period;

generating a bid uncertainty control adjustment value based on the adjusted model and a bid uncertainty value associated with the earlier time period;

generating a bid price and a bid uncertainty for each candidate promotion;

for each open promotion slot, performing a market clearing process using at least one candidate promotion, using a bid price and a bid uncertainty associated with each candidate promotion; and

serving at least one of the candidate promotions based on the results of the market clearing process.

9. The computer-readable storage medium of claim 8, wherein generating a bid price and a bid uncertainty for each candidate promotion comprises:

generating a probabilistic model estimating engagement data associated with the candidate promotion, the probabilistic model associated with an expected value and an expected variance;

generating the bid price, based on the expected value and the bid price control adjustment value; and

generating the bid uncertainty value, based on the expected variance and the bid uncertainty control adjustment value.

10. The computer-readable storage medium of claim 8, wherein the market clearing process comprises:

determining that at least one candidate promotion is bidding for an impression;

for each candidate promotion bidding for the impression;

generating, based on the associated bid price value and the associated bid price control adjustment value, a nominal bid price;

generating, based on the associated bid uncertainty value and the associated bid uncertainty control adjustment value, a nominal bid uncertainty;

generating a final bid for the candidate promotion using the nominal bid price and the nominal bid uncertainty;

identifying the highest bid of the final bids;

determining if a bid allocation value associated with the candidate promotion is greater than a generated random value; and

if so, outputting the candidate promotion corresponding to the highest bid.

11. The computer-readable storage medium of claim 8, wherein:

each partition is associated with a plant gain factor (K_p)and a controller gain factor (K_c(k)), where K_p and K_c(k) are related to one another in an inverse relationship; and

generating the bid uncertainty control adjustment value is further based on the controller gain factor K_c(k).

12. The computer-readable storage medium of claim 8, wherein the control data comprises data on a desired number of engagements for content promotions associated with a partition.

13. The computer-readable storage medium of claim 8, wherein the medium causes the at least one electronic processor to perform the operation of generating a factor based on the adjusted model and the previous engagement data, and

wherein generating a bid price control adjustment value is based on the generated factor.

14. The computer-readable storage medium of claim 8, wherein:

the market clearing process is performed in response to a user requesting a web page, the web page containing at least one promotion slot, and

wherein serving the at least one candidate promotion comprises inserting the at least one candidate promotion into the at least one promotion slot on the web page.

15. A system for control, comprising:

at least one electronic processor; and

a storage device that stores instructions that, when executed by the at least one electronic processor, causes the at least one electronic processor to perform the following operations;

receiving at least one candidate promotion and at least one partition, at least one of the candidate promotions associated with at least one partition;

receiving control data and previous engagement data associated with the at least one partition, the previous engagement data associated with an earlier time period;

for each partition;

generating an adjusted model of the control data over a first time period, based on data representing a traffic pattern;

generating a bid price control adjustment value based on the adjusted model and a bid price value associated with an earlier time period;

generating a bid uncertainty control adjustment value based on the adjusted model and a bid uncertainty value associated with an earlier time period;

generating a bid price and a bid uncertainty for each candidate promotion;

for each open promotion slot, performing a market clearing process using at least one candidate promotion, using a bid price and a bid uncertainty associated with each candidate promotion; and

serving at least one of the candidate promotions based on the results of the market clearing process.

16. The system of claim 15, wherein generating a bid price and a bid uncertainty for each candidate promotion comprises:

generating a probabilistic model estimating engagement data associated with the candidate promotion, the probabilistic model associated with an expected value and an expected variance;

generating the bid price, based on the expected value and the bid price control adjustment value; and

generating the bid uncertainty value, based on the expected variance and the bid uncertainty control adjustment value.

17. The system of claim 15, wherein the market clearing process comprises:

determining that at least one candidate promotion is bidding for an impression;

for each candidate promotion bidding for the impression;

generating, based on the associated bid price value and the associated bid price control adjustment value, a nominal bid price;

generating, based on the associated bid uncertainty value and the associated bid uncertainty control adjustment value, a nominal bid uncertainty;

generating a final bid for the candidate promotion using the nominal bid price and the nominal bid uncertainty;

identifying the highest bid of the final bids;

determining if a bid allocation value associated with the candidate promotion is greater than a generated random value; and

if so, outputting the candidate promotion corresponding to the highest bid.

18. The system of claim 15, wherein:

each partition is associated with a plant gain factor (K_p)and a controller gain factor (K_c(k)), where K_p and K_c(k) are related to one another in an inverse relationship; and

generating the bid uncertainty control adjustment value is further based on the controller gain factor K_c(k).

19. The system of claim 15, wherein the instructions cause the at least one electronic processor to perform the operation of generating a factor based on the adjusted model and the previous engagement data, and

wherein generating a bid price control adjustment value is based on the generated factor.

20. The system of claim 15, wherein:

the market clearing process is performed in response to a user requesting a web page, the web page containing at least one promotion slot, and

wherein serving the at least one candidate promotion comprises inserting the at least one candidate promotion into the at least one promotion slot on the web page.