Private Computation of Multi-Touch Attribution
AssigneeMarin Software Incorporated
InventorWister Walcott
Life of this patent
Estimating the term…
Abstract
A plurality of anonymized publisher-user identifiers are received at a processor, and a plurality of anonymized advertiser-user identifiers are received from an advertiser at the processor. Without de-anonymizing any publisher-user identifiers in the received plurality of publisher-user identifiers and any advertiser-user identifiers in the received plurality of advertiser-user identifiers, the processor obliviously computes an intersection among the received publisher-user identifiers and the received ad-user identifiers to create an intersection set containing a plurality of advertiser-user identifiers matched with publisher-user identifiers.
Claims20
A method, comprising:
- receiving, at a processor, from a plurality of ad publishers, a plurality of anonymized publisher-user identifiers;
- receiving, at the processor, from an advertiser, a plurality of anonymized advertiser-user identifiers;
- at the processor, without de-anonymizing any publisher-user identifiers in the received plurality of publisher-user identifiers and any advertiser-user identifiers in the received plurality of advertiser-user identifiers, obliviously computing an intersection among the received publisher-user identifiers and the received ad-user identifiers to create an intersection set containing a plurality of advertiser-user identifiers matched with publisher-user identifiers;
- for each computed intersection in the intersection set, obliviously computing a conversion value based on a conversion model, creating a conversion data set;
- aggregating the data in the conversion data set, creating an aggregated data set that includes a total aggregated conversion credit value where each value is specific to an Ad ID but aggregated across all ad publishers and users;
- calculating an advertising recommendation, based on the aggregated conversion credit value;
- and
- sending the calculated advertising recommendation to an advertising entity.
A method, comprising:
- receiving, at a processor, a plurality of anonymized publisher-user identifiers;
- receiving, at the processor, a plurality of anonymized advertiser-user identifiers;
- at the processor, without de-anonymizing any publisher-user identifiers in the received plurality of publisher-user identifiers and any advertiser-user identifiers in the received plurality of advertiser-user identifiers, obliviously computing an intersection among the received publisher-user identifiers and the received ad-user identifiers to create an intersection set containing at least one computed intersection among the plurality of advertiser-user identifiers and the publisher-user identifiers;
- aggregating a plurality of data in the conversion data set, creating an aggregated data set;
- and
- calculating an advertising recommendation based on the aggregated data set.
A method comprising:
- receiving a set of anonymized user IDs from an advertiser;
- receiving a set of anonymized user IDs from an advertising publisher, the anonymized user IDs from the advertising publisher being anonymized by the same method as the anonymized user IDs from the advertiser;
- obliviously computing an intersection among the anonymized user IDs to determine a set of matches between each anonymized user ID from the advertiser and each anonymized user ID from the advertising publisher;
- assigning a conversion credit value to each match in the set of matches, the conversion credit value being based on a predetermined set of ad-interaction data rules;
- aggregating the conversion credit values across all matches to create an aggregation set;
- sending the aggregation set to the advertiser to use in determining a value of the first advertising publisher.
Dependencies are inferred from the claim text.