Systems and methods for privacy preserving determination of intersections of sets of user identifiers

Abstract

At least one aspect is directed to determining an estimate of an intersection of user identifiers in a first set of user identifiers and a second set of user identifiers. The first and second sets of user identifiers can be populated with user identifiers that have interacted with the same content item or content item campaign. Estimates of intersections of the first and the second sets can be determined based on a binomial vector approach, a vector of counts approach, or a hybrid approach. The binomial vector approach generates vectors based on k hashes of each user identifier in the first set and summing the vectors to generate a first vector. The intersection can be determined based on a dot product of the first vector and a second vector similarly generated from the second set of user identifiers.

1 . A method for estimating the number of unique user interactions with a set of content items provided by different content delivery platforms comprising:
 transmitting, via a network, a set of hash functions to a first content delivery platform;   transmitting, via a network, the set of hash functions to a second content delivery platform;   receiving, via a network, a first vector from the first content delivery platform, each coordinate of the first vector being equal to a sum based on a plurality of hashes, with each hash calculated from one of a plurality of user interactions with the set of content items occurring via the first content delivery platform;   receiving, via a network, a second vector from the second content delivery platform, each coordinate of the second vector being equal to a sum based on a plurality of hashes, with each hash calculated from one of a plurality of user interactions with the set of content items occurring via the second content delivery platform;   estimating a number of user interactions with the set of content items occurring via the first content delivery platform based on a sum of the elements of the first vector;   estimating a number of user interactions with the set of content items occurring via the second content delivery platform based on a sum of the elements of the second vector; and   estimating a number of unique user interactions with the set of content items provided by both the first content delivery platform and the second content delivery platform based on the number of user interactions with the set of content items occurring via the first content delivery platform, the number of user interactions with the set of content items occurring via the second content delivery platform, the first vector, and the second vector.   
     
     
         2 . The method of  claim 1 , wherein receiving the first vector from the first content delivery platform includes receiving the number of user interactions occurring via the first content delivery platform. 
     
     
         3 . The method of  claim 1 , wherein receiving the second vector from the second content delivery platform includes receiving the number of user interactions occurring via the second content delivery platform. 
     
     
         4 . The method of  claim 1 , wherein receiving the first vector from the first content delivery platform comprises receiving a first plurality of vectors from the first content delivery platform, wherein each of the first plurality of vectors corresponds to one hash in the set of hash functions. 
     
     
         5 . The method of  claim 4 , wherein receiving the second vector from the second content delivery platform comprises receiving a second plurality of vectors from the second content delivery platform, wherein each of the second plurality of vectors corresponds to one hash in the set of hash functions. 
     
     
         6 . The method of  claim 5 , wherein estimating the number of unique user interactions is based on the average of the dot product of each vector in the first and second plurality of vectors. 
     
     
         7 . The method of  claim 1 , wherein estimating the number of user interactions with the set of content items occurring via the first content delivery platform is based on the sum of each coordinate of the first vector. 
     
     
         8 . The method of  claim 1 , wherein estimating the number of user interactions with the set of content items occurring via the second content delivery platform is based on the sum of each coordinate of the second vector. 
     
     
         9 . The method of  claim 1 , wherein estimating the number of unique user interactions with the set of content items occurring via the first and second content delivery platforms is based on determining a covariance between the first vector and the second vector. 
     
     
         10 . The method of  claim 1 , wherein estimating the number of unique user interactions comprises subtracting the dot product of the first vector and the second vector from the sum of the number of user interactions with occurring via the first content delivery platform and the number of user interactions occurring via the second content delivery platform. 
     
     
         11 . A system comprising one or more processors, the processors configured to:
 transmit, via a network, a set of hash functions to a first content delivery platform;   transmit, via a network, the set of hash functions to a second content delivery platform;   receive, via a network, a first vector from the first content delivery platform, each coordinate of the first vector being equal to a sum based on a plurality of hashes, with each hash calculated from one of a plurality of user interactions with the set of content items occurring via the first content delivery platform;   receive, via a network, a second vector from the second content delivery platform, each coordinate of the second vector being equal to a sum based on a plurality of hashes, with each hash calculated from one of a plurality of user interactions with the set of content items occurring via the second content delivery platform;   estimate a number of user interactions with the set of content items occurring via the first content delivery platform based on a sum of the elements of the first vector;   estimate a number of user interactions with the set of content items occurring via the second content delivery platform based on a sum of the elements of the second vector; and   estimate a number of unique user interactions with the set of content items provided by both the first content delivery platform and the second content delivery platform based on the number of user interactions with the set of content items occurring via the first content delivery platform, the number of user interactions with the set of content items occurring via the second content delivery platform, the first vector, and the second vector.   
     
     
         12 . The system of  claim 11 , wherein the one or more processors are configured to: receive the first vector from the first content delivery platform, and receive the number of user interactions occurring via the first content delivery platform. 
     
     
         13 . The system of  claim 11 , wherein the one or more processors are configured to: receive the second vector from the second content delivery platform, and receive the number of user interactions occurring via the second content delivery platform. 
     
     
         14 . The system of  claim 11 , wherein the one or more processors are configured to: receive a first plurality of vectors from the first content delivery platform, wherein each of the first plurality of vectors corresponds to one hash in the set of hash functions. 
     
     
         15 . The system of  claim 14 , wherein the one or more processors are configured to: receive a second plurality of vectors from the second content delivery platform, wherein each of the second plurality of vectors corresponds to one hash in the set of hash functions. 
     
     
         16 . The system of  claim 15 , wherein the one or more processors are configured to: estimate the number of unique user interactions based on the average of the dot product of each vector in the first and second plurality of vectors. 
     
     
         17 . The system of  claim 11 , wherein the one or more processors are configured to: estimate the number of user interactions with the set of content items occurring via the first content delivery platform based on the sum of each coordinate of the first vector. 
     
     
         18 . The system of  claim 11 , wherein the one or more processors are configured to: estimate the number of user interactions with the set of content items occurring via the second content delivery platform based on the sum of each coordinate of the second vector. 
     
     
         19 . The system of  claim 11 , wherein the one or more processors are configured to: estimate the number of unique user interactions with the set of content items occurring via the first and second content delivery platforms based on a covariance between the first vector and the second vector. 
     
     
         20 . The system of  claim 11 , wherein the one or more processors are configured to: estimate the number of unique user interactions based on subtracting the dot product of the first vector and the second vector from the sum of the number of user interactions occurring via the first content delivery platform and the number of user interactions occurring via the second content delivery platform.