SECURE MULTI-PARTY REACH AND FREQUENCY ESTIMATION

    公开(公告)号:US20210359836A1

    公开(公告)日:2021-11-18

    申请号:US17278496

    申请日:2020-07-07

    Applicant: GOOGLE LLC

    Abstract: Systems and methods for generating min-increment counting bloom filters to determine count and frequency of device identifiers and attributes in a networking environment are disclosed. The system can maintain a set of data records including device identifiers and attributes associated with device in a network. The system can generate a vector comprising coordinates corresponding to counter registers. The system can identify hash functions to update a counting bloom filter. The system can hash the data records to extract index values pointing to a set of counter registers. The system can increment the positions in the min-increment counting bloom filter corresponding to the minimum values of the counter registers. The system can obtain an aggregated public key comprising a public key. The system can encrypt the counter registers using the aggregated shared key to generate an encrypted vector. The system can transmit the encrypted vector to a networked worker computing device.

    REACH AND FREQUENCY PREDICTION FOR DIGITAL COMPONENT TRANSMISSIONS

    公开(公告)号:US20230410034A1

    公开(公告)日:2023-12-21

    申请号:US17845778

    申请日:2022-06-21

    Applicant: Google LLC

    CPC classification number: G06Q10/087 G06N7/005

    Abstract: In one aspect, there is provided a method that includes: obtaining multiple input frequency histograms that each correspond to a respective transmission commitment, where a transmission commitment corresponds to a subset of publishers from a set of publishers; generating a frequency model based on the input frequency histograms, where the frequency model is a parametric model parameterized by a set of model parameters that include a correlation matrix with a respective correlation value for each pair of publishers from the set of publishers; receiving a request to predict a frequency histogram for a target transmission commitment corresponding to a target subset of publishers; generating a predicted frequency histogram for the target transmission commitment using the frequency model; and generating one or more predictions characterizing the target transmission commitment using the predicted frequency histogram.

    Secure Multi-Party Reach and Frequency Estimation

    公开(公告)号:US20240372704A1

    公开(公告)日:2024-11-07

    申请号:US18769226

    申请日:2024-07-10

    Applicant: Google LLC

    Abstract: Systems and methods for generating min-increment counting bloom filters to determine count and frequency of device identifiers and attributes in a networking environment are disclosed. The system can maintain a set of data records including device identifiers and attributes associated with device in a network. The system can generate a vector comprising coordinates corresponding to counter registers. The system can identify hash functions to update a counting bloom filter. The system can hash the data records to extract index values pointing to a set of counter registers. The system can increment the positions in the min-increment counting bloom filter corresponding to the minimum values of the counter registers. The system can obtain an aggregated public key comprising a public key. The system can encrypt the counter registers using the aggregated shared key to generate an encrypted vector. The system can transmit the encrypted vector to a networked worker computing device.

    SECURE MULTI-PARTY REACH AND FREQUENCY ESTIMATION

    公开(公告)号:US20220376887A1

    公开(公告)日:2022-11-24

    申请号:US17278626

    申请日:2020-07-07

    Applicant: GOOGLE LLC

    Abstract: Systems and methods for generating min-increment counting bloom filters to determine count and frequency of device identifiers and attributes in a networking environment are disclosed. The system can maintain a set of data records including device identifiers and attributes associated with device in a network. The system can generate a vector comprising coordinates corresponding to counter registers. The system can identify hash functions to update a counting bloom filter. The system can hash the data records to extract index values pointing to a set of counter registers. The system can increment the positions in the min-increment counting bloom filter corresponding to the minimum values of the counter registers. The system can obtain an aggregated public key comprising a public key. The system can encrypt the counter registers using the aggregated shared key to generate an encrypted vector. The system can transmit the encrypted vector to a networked worker computing device.

    CARDINALITY MODELS FOR PRIVACY-SENSITIVE ASSESSMENT OF DIGITAL COMPONENT TRANSMISSION REACH

    公开(公告)号:US20240005040A1

    公开(公告)日:2024-01-04

    申请号:US17856084

    申请日:2022-07-01

    Applicant: Google LLC

    CPC classification number: G06F21/6263 G06F16/24558 G06F21/6227

    Abstract: In one aspect, there is provided a method performed by one or more computers for privacy-sensitive assessment of digital component transmission reach based on cardinalities of subset unions of a collection of user sets, the method including: receiving a request to determine a number of users that are included in a target group of users that received at least one transmission of a digital component, where the request includes a set expression defined in terms of the collection of user sets, generating an alternative representation of the set expression in terms of primitive sets, applying a cardinality model to each primitive to generate a cardinality of each primitive set as a linear combination of cardinalities of subset unions of the collection of user sets, and determining the number of users included in the target group of users based on the cardinalities of the primitive sets.

    REACH AND FREQUENCY PREDICTION FOR DIGITAL COMPONENT TRANSMISSIONS

    公开(公告)号:US20230409773A1

    公开(公告)日:2023-12-21

    申请号:US17845827

    申请日:2022-06-21

    Applicant: Google LLC

    CPC classification number: G06F30/20 G06F2111/08

    Abstract: In one aspect, there is provided a method performed by one or more computers that includes: obtaining an observed frequency histogram corresponding to an observed transmission commitment, where a transmission commitment specifies a number of transmissions of a digital component; generating a frequency model based on the observed frequency histogram, where the frequency model is a parametric model parameterized by a set of model parameters; receiving a request to predict a frequency histogram corresponding to a target transmission commitment; processing data defining the target transmission commitment using the frequency model to generate a predicted frequency histogram corresponding to the target transmission commitment; and generating one or more predictions characterizing the target transmission commitment using the predicted frequency histogram.

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