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    • 6. 发明申请
    • Private Computation of Multi-Touch Attribution
    • US20220405800A1
    • 2022-12-22
    • US17895935
    • 2022-08-25
    • Marin Software Incorporated
    • Wister WalcottHenry Corrigan-Gibbs
    • G06Q30/02H04L9/08G06F21/60
    • A method comprises receiving an ad event data including data about a plurality of ad events, and including a user ID and an ad ID for each ad event in the ad event data set, where the ad event data set has been anonymized applying a one-way encryption key for each user ID in the ad event data set, and a two-way encryption key for the ad ID in the ad event data set. The attribution processor receives a customer data set including data about a plurality of customers, including a user ID and a customer value for each customer, where the customer data set has been anonymized using the one-way encryption key for each user ID in the data, and a private encryption key for the customer value. Without decrypting the received ad event data set and the received customer data set, the processor then matches ad events for each conversion by comparing the user IDs in the encrypted ad event data set to the user IDs in the encrypted customer data set to create a set of contributing ad events, assigns a share of the customer value to each relevant ad event, sums homomorphically the encrypted customer values for contributing events, and determines a recommendation for serving advertisements.