Optimizing Advertisement Campaign Servicing

• US 20090327075A1
• Filed: 06/27/2008
• Published: 12/31/2009
• Est. Priority Date: 06/27/2008
• Status: Abandoned Application

• Current Assignee: RPX Corporation
• Original Assignee: Nokia Corporation
• Inventors: Kosuru, Yekesa, Saadat, Saied
• Application Number:
  US12/147,991
• Publication Number:
  US 20090327075A1
• Time in Patent Office: Days
• US Class Current: 705/14.53
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0257 User requested

Abstract

Methods, system and computer readable media for distributing advertisements include minimizing storage costs for frequency capping, dividing a set of campaigns into slices and predetermining campaign-target matches. Frequency storage costs may be minimized by storing frequency data for those users or groups of users that have a high probability of exceeding a frequency limit. Additionally or alternatively, a set of campaigns may be divided into slices. Less than all of the slices may then be evaluated (i.e., instead of the entire set) against a user requesting an advertisement. Still further, all campaign-target matches may be evaluated prior to receiving advertisement requests. Re-evaluations may be performed when changes occur to the set of campaigns. The match data may be stored in bitset, hash map and bitmap storage structures.

Claims

1. A method comprising:

receiving a request for an advertisement in a set of advertisements;

upon receiving the advertisement request, determining whether user-campaign match data for the set of advertisements and a set of users has been previously determined; and

in response to determining that user-campaign match data has previously been determined, selecting an advertisement with which to respond to the request using the previously determined user-campaign match data.

2. The method of claim 1, further comprising, in response to determining that the user-campaign match data has not been previously determined, determining the user-campaign match data including one or more matches between a set of one or more users and the set of advertisements.

3. The method of claim 1, further comprising storing the user-campaign match data in at least one bitset, wherein each advertisement in the set of advertisements corresponds to a different position in the at least one bitset.

4. The method of claim 3, further comprising, for each advertisement, storing, in at least another bitset, an identifier of the advertisement in association with the advertisement'"'"'s corresponding position in the at least one bitset.

5. The method of claim 4, further comprising:

determining a user associated with the request;

determining a bitset from the at least one bitset corresponding to the user;

determining one or more positions in the determined bitset indicating a match; and

identifying one or more advertisements corresponding to the one or more positions using the at least another bitset.

6. The method of claim 5, wherein the user-campaign match data is stored in a plurality of bitsets, each bitset corresponding to a different user in the set of users and wherein the plurality of bitsets are stored in a hash map keyed to user identifiers corresponding to each user in the set of users.

7. The method of claim 4, further comprising:

determining that an advertisement has been removed from the set of advertisements; and

storing an indicator in a position of the bitmap corresponding to the removed advertisement indicating that the position is empty.

8. The method of claim 4, further comprising:

determining that a new advertisement is to be added;

determining a position in the bitmap having an empty indicator; and

storing an identifier of the new advertisement in the determined position having the empty indicator.

9. The method of claim 1, further comprising:

prior to receiving the request, dividing the set of advertisements into a plurality of subsets, wherein selecting an advertisement with which to respond to the request using the previously determined user-campaign match data includes;

selecting at least one subset from the plurality of subsets, wherein only the user-campaign match data of the advertisements in the selected at least one subset is used to select the advertisement.

10. The method of claim 1, further comprising:

determining a probability that the advertisement will be sent to a user associated with the request a number of times within a specified period of time exceeding a predefined limit;

determining whether the probability exceeds a threshold probability; and

in response to determining that the probability exceeds the threshold probability, storing transmission frequency data for the advertisement.

11. The method of claim 10, wherein the stored transmission frequency data includes only a transmission frequency of the advertisement to the user.

12. The method of claim 10, wherein the probability is determined prior to receiving the advertisement request.

13. A method comprising:

dividing a set of advertisements into a plurality of subsets, wherein each subset is smaller than the set;

receiving an advertisement request;

selecting at least one subset from the plurality of subsets; and

determining one or more advertisements matching the request by comparing one or more advertisements in the selected at least one subset to the request.

14. The method of claim 13, wherein dividing the set of advertisements into the plurality of subsets is based on a percentage of a user population that each advertisement in the set of advertisements matches.

15. The method of claim 13, wherein dividing the set of advertisements into the plurality of subsets is based on one or more display parameters of each advertisement in the set of advertisements.

16. The method of claim 13, wherein the request includes demographic information of a user associated with the request.

17. A method comprising:

determining a probability that an advertisement will be sent to a user a number of times, over a specified period of time, exceeding a predefined limit;

determining whether the probability exceeds a threshold probability; and

in response to determining that the probability exceeds the threshold probability, storing transmission frequency data for the advertisement.

18. The method of claim 17, wherein in response to determining that the probability does not exceed the threshold probability, not storing the transmission frequency data.

19. The method of claim 17, further comprising:

determining a usage pattern of the user; and

categorizing the user according to the determined usage pattern, wherein determining the probability that the advertisement will be sent to the user a number of times, over the specified period of time, exceeding a predefined limit is based on the determined usage pattern.

20. The method of claim 17, wherein the threshold probability corresponds to a confidence level.

21. The method of claim 17, wherein the transmission frequency data of the advertisement only includes transmission frequency data of transmissions of the advertisement to the users in the category of users during the specified period of time.

22. An apparatus comprising:

a processor; and

memory configured to store computer readable instructions that, when executed, causes the processor to perform a method comprising;

determining a probability that an advertisement will be sent to a user a number of times, over a specified period of time, exceeding a predefined limit;

determining whether the probability exceeds a threshold probability; and

in response to determining that the probability exceeds the threshold probability, storing transmission frequency data for the advertisement.

23. The apparatus of claim 22, wherein in response to determining that the probability does not exceed the threshold probability, not storing the transmission frequency data.

24. The apparatus of claim 22, the memory further configured to store instructions for:

determining a usage pattern of the user; and

categorizing the user according to the determined usage pattern, wherein determining the probability that the advertisement will be sent to the user a number of times, over the specified period of time, exceeding a predefined limit is based on the determined usage pattern.

25. An apparatus comprising:

a processor; and

memory configured to store computer readable instructions that, when executed, causes the processor to perform a method comprising;

dividing a set of advertisements into a plurality of subsets, wherein each subset is smaller than the set;

receiving an advertisement request;

selecting at least one subset from the plurality of subsets; and

determining one or more advertisements matching the request by comparing one or more advertisements in the selected at least one subset to the request.

26. The apparatus of claim 25, wherein dividing the set of advertisements into the plurality of subsets is based on a percentage of a user population that each advertisement in the set of advertisements matches.

27. The apparatus of claim 25, wherein dividing the set of advertisements into the plurality of subsets is based on display frequency requirements of each advertisement in the set of advertisements.

28. An apparatus comprising:

a processor; and

memory configured to store computer readable instructions that, when executed, causes the processor to perform a method comprising;

receiving a request for an advertisement in a set of advertisements;

upon receiving the advertisement request, determining whether user-campaign match data for the set of advertisements and a set of users has been previously determined; and

in response to determining that user-campaign match data has previously been determined, selecting an advertisement with which to respond to the request using the previously determined user-campaign match data.

29. The apparatus of claim 28, the memory further configured to store instructions for, in response to determining that the user-campaign match data has not been previously determined, determining the user-campaign match data including one or more matches between a set of one or more users and the set of advertisements.

30. The apparatus of claim 29, the memory further configured to store instructions for, for each advertisement, storing, in a bitmap, an identifier of the advertisement in association with the advertisement'"'"'s corresponding position in the at least one bitset

31. One or more computer readable media storing computer readable instructions that, when executed by a processor, cause the processor to perform a method comprising:

determining a probability that an advertisement will be sent to a user a number of times exceeding a predefined limit;

determining whether the probability exceeds a threshold probability; and

in response to determining that the probability exceeds the threshold probability, storing transmission frequency data for the advertisement.

32. The one or more computer readable media of claim 31, wherein in response to determining that the probability does not exceed the threshold probability, not storing the transmission frequency data.

33. The one or more computer readable media of claim 31, further comprising instructions for:

determining a usage pattern of the user; and

categorizing the user according to the determined usage pattern, wherein determining the probability that the advertisement will be sent to the user a number of times exceeding a predefined limit is based on the determined usage pattern.

34. One or more computer readable media storing computer readable instructions that, when executed by a processor, cause the processor to perform a method comprising:

dividing a set of advertisements into a plurality of subsets, wherein each subset is smaller than the set;

receiving an advertisement request;

selecting at least one subset from the plurality of subsets; and

determining one or more advertisements matching the request by comparing one or more advertisements in the selected at least one subset to the request.

35. The one or more computer readable media of claim 34, wherein dividing the set of advertisements into the plurality of subsets is based on a percentage of a user population that each advertisement in the set of advertisements matches.

36. The one or more computer readable media of claim 34, wherein dividing the set of advertisements into the plurality of subsets is based on display frequency requirements of each advertisement in the set of advertisements.

37. One or more computer readable media storing computer readable instructions that, when executed by a processor, cause the processor to perform a method comprising:

receiving a request for an advertisement in a set of advertisements;

upon receiving the advertisement request, determining whether user-campaign match data for the set of advertisements and a set of users has been previously determined; and

in response to determining that user-campaign match data has previously been determined, selecting an advertisement with which to respond to the request using the previously determined user-campaign match data.

38. The one or more computer readable media of claim 37, further comprising instructions for, in response to determining that the user-campaign match data has not been previously determined, determining the user-campaign match data including one or more matches between a set of one or more users and the set of advertisements.

39. The one or more computer readable media of claim 37, further comprising instructions for, for each advertisement, storing, in a bitmap, an identifier of the advertisement in association with the advertisement'"'"'s corresponding position in the at least one bitset.