Abstract: A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Abstract: A method, system, and computer program product for managing user identification codes in an internet advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.

Abstract: A method, system, and computer program product for managing user identification codes in an interne advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.

Abstract: Techniques are provided to quickly process stored objects to generate an accurate estimate of the number of live objects that will be responsive to a client's filtering request defined at least in part based on a filtering parameter. Stored objects generated from user interactions with webpages are modified to simulate live objects and processed by a live object-intake simulator. The simulated results are then filtered using the filtering parameter to form a subset of matching objects. An estimate of the number of live objects produced by the filtering parameter is generated using at least the count of the objects in the subset. A confidence metric of the estimate is computed, in some cases using a statistical model. Under certain conditions, the estimate is delivered, the confidence metric is delivered, and/or live object intake based on the filtering parameter is initiated.

Abstract: Techniques are provided for accurately and quickly processing distributed stored objects to provide a timely and accurate prediction of the number of live objects a parameterized file request will produce. Stored objects representing previous user webpage visit interactions are stored in different storage locations in a data store. The stored objects at each storage location are processed in parallel by hashing stored objects with a hash function such that they are spread somewhat uniformly into buckets. Sub-buckets in each bucket are formed that correspond to selected category identifiers. Also in parallel, K-minimum values are computed for each sub-bucket to estimate the count of stored objects in the data store. The K-minimum values for sub-buckets corresponding to the same category ID across all buckets are combined, in some cases harmonically, and used to generate a predicted number of live objects responsive to a parameterized file request.

Abstract: A method, system, and computer program product for managing user identification codes in an internet advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.

Abstract: A method, system, and computer program product for managing user identification codes in an internet advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.

Abstract: A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Abstract: A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Abstract: A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Abstract: Techniques are provided to quickly process stored objects to generate an accurate estimate of the number of live objects that will be responsive to a client's filtering request defined at least in part based on a filtering parameter. Stored objects generated from user interactions with webpages are modified to simulate live objects and processed by a live object-intake simulator. The simulated results are then filtered using the filtering parameter to form a subset of matching objects. An estimate of the number of live objects produced by the filtering parameter is generated using at least the count of the objects in the subset. A confidence metric of the estimate is computed, in some cases using a statistical model. Under certain conditions, the estimate is delivered, the confidence metric is delivered, and/or live object intake based on the filtering parameter is initiated.

Abstract: Techniques are provided for accurately and quickly processing distributed stored objects to provide a timely and accurate prediction of the number of live objects a parameterized file request will produce. Stored objects representing previous user webpage visit interactions are stored in different storage locations in a data store. The stored objects at each storage location are processed in parallel by hashing stored objects with a hash function such that they are spread somewhat uniformly into buckets. Sub-buckets in each bucket are formed that correspond to selected category identifiers. Also in parallel, K-minimum values are computed for each sub-bucket to estimate the count of stored objects in the data store. The K-minimum values for sub-buckets corresponding to the same category ID across all buckets are combined, in some cases harmonically, and used to generate a predicted number of live objects responsive to a parameterized file request.

Abstract: A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Abstract: A method, system, and computer program product for managing user identification codes in an internet advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.

Abstract: A server receives incoming data records comprising an ID value and respective user attributes corresponding to a user activity that originates at a user device. Characteristics of the activity and/or characteristics of the user device are considered in order to assign a probabilistic confidence value, which is in turn used to generate links from an incoming data record to other previously-received data records, and in so doing, generates a probabilistic link between one set of user attributes from the incoming data record and another set of user attributes from previously-received data records. A messaging campaign specification that describes target user attributes is used to identify a matching set of target audience member records. The determination of a match or not is based on the probabilistic confidence value and a threshold can be varied to extend audience reach. The identified set of target audience member records are transmitted over a network.

Abstract: A method, system, and computer program product for managing user identification codes in an internet advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.