Abstract: Change detection and updates using probabilistic data structures are described. In one or more examples, a change is detected to a dataset record that is used as a basis to generate a first sketch as a probabilistic data structure. A second sketch is generated as a probabilistic data structure based on the change to the dataset record. The first sketch is replaced with the second sketch as stored in a database, the database supporting a probabilistic result to a query operation.

Abstract: Data enrichment and identity translation techniques using probabilistic data structures are described. In one or more examples, a plurality of datasets are received from a plurality of entities. Each dataset has a plurality of dataset records describing a respective audience. A plurality of sets of sketches are generated as probabilistic data structures, respectively, based on the plurality of datasets. A result is formed by processing a query. The result includes at least one sketch having a probabilistic data structure generated based on one or more of the plurality of sets of sketches. An entity is identified from the plurality of entities corresponding to the at least one sketch and entity is exposed for display in a user interface.

Abstract: Differential privacy techniques using probabilistic data structures are described. In one or more examples, a dataset record is received and a sketch is generated as a probabilistic data structure by applying noise to the dataset record. The sketch is communicated to be stored in a database that supports a probabilistic result to a query operation.

Abstract: Methods and systems are provided for evaluating edges of collapsed identity graphs for identity resolution. In embodiments described herein, a collapsed state of identity graphs, such as based on an identity namespace limit being exceeded by the identity graphs, is determined by applying an identity node and edge of an incoming record to the identity graphs. A temporary state of the identity graphs is determined by pruning edges of the collapsed state. A non-collapsed state of the identity graphs that includes the edge of the incoming record is determined by applying the edge of the incoming record to the temporary state. A different edge is determined to be pruned from the non-collapsed state as when the different edge is applied to the temporary state with the edge of the incoming record, the temporary state collapses into the collapsed state. An identity graph is updated based on the non-collapsed state.

Abstract: An audience analysis system using probabilistic data structure is described. In one or more examples, a targeted dataset is received from a first entity. The targeted dataset has a plurality of target dataset records describing a target audience subject to a targeted content control strategy. A targeted set of sketches is generated as probabilistic data structures based on the targeted dataset. A realized dataset is received from a second entity. The realized dataset has a plurality of realized dataset records describing digital content exposure of a realized audience to the targeted content control strategy. A realized set of sketches is generated as probabilistic data structures based on the realized dataset. The targeted set of sketches and the realized set of sketches are then stored in one or more databases in support of one or more operations, execution of which generates a probabilistic result to a query.

Abstract: A collaboration system using probabilistic data structures is described. In one or more examples, a query is formed for processing by a database in a shared environment. A probabilistic result is received from the database to the query. The query involves processing a first sketch from a first entity and a second sketch from a second entity maintained in the shared environment. Confidential information associated with the first entity is resolved in a first protected environment based on a mapping of the confidential information to the first sketch. The probabilistic result and the confidential information are then exposed to the first entity. Activation data is configured by the first entity. The activation data usable by the second entity to resolve one or more members associated with confidential information from the second entity in a second protected environment.

Abstract: Data privacy management techniques using probabilistic data structures are described. In one or more examples, a dataset record is received that includes an identity key, a respective attribute, and confidential information. A sketch is generated as a probabilistic data structure based on the identity key and the attribute. A mapping is formed of the confidential information to the sketch. The sketch is communicated to be stored in a database that supports a probabilistic result to a query operation.

Abstract: Data privacy management techniques using probabilistic data structures are described. In one or more examples, a dataset record is received that includes an identity key, a respective attribute, and confidential information. A sketch is generated as a probabilistic data structure based on the identity key and the attribute. A mapping is formed of the confidential information to the sketch. The sketch is communicated to be stored in a database that supports a probabilistic result to a query operation.

Abstract: Systems and methods for dynamic user profile management are provided. One aspect of the systems and methods includes receiving, by a lookup component, a request for a user profile; computing, by a profile component, a time-to-live (TTL) refresh value for the user profile based on a lookup history of the user profile; updating, by the profile component, a TTL value of the user profile based on the request and the TTL refresh value; storing, by the profile component, the user profile and the updated TTL value in the edge database; and removing, by the edge database, the user profile from the edge database based on the updated TTL value.

Abstract: Systems and methods for dynamic user profile projection are provided. One or more aspects of the systems and methods includes computing, by a prediction component, a predicted number of lookups for a future time period based on a lookup history of a user profile using a lookup prediction model; comparing, by the prediction component, the predicted number of lookups to a lookup threshold; and transmitting, by a projection component, the user profile to an edge server based on the comparison.

Abstract: Systems and methods for dynamic user profile management are provided. One aspect of the systems and methods includes receiving, by a lookup component, a request for a user profile; computing, by a profile component, a time-to-live (TTL) refresh value for the user profile based on a lookup history of the user profile; updating, by the profile component, a TTL value of the user profile based on the request and the TTL refresh value; storing, by the profile component, the user profile and the updated TTL value in the edge database; and removing, by the edge database, the user profile from the edge database based on the updated TTL value.

Abstract: Systems and methods for dynamic user profile projection are provided. One or more aspects of the systems and methods includes computing, by a prediction component, a predicted number of lookups for a future time period based on a lookup history of a user profile using a lookup prediction model; comparing, by the prediction component, the predicted number of lookups to a lookup threshold; and transmitting, by a projection component, the user profile to an edge server based on the comparison.

Abstract: Systems and methods for dynamic user profile management are provided. One aspect of the systems and methods includes receiving, by a lookup component, a request for a user profile; computing, by a profile component, a time-to-live (TTL) refresh value for the user profile based on a lookup history of the user profile; updating, by the profile component, a TTL value of the user profile based on the request and the TTL refresh value; storing, by the profile component, the user profile and the updated TTL value in the edge database; and removing, by the edge database, the user profile from the edge database based on the updated TTL value.

Abstract: Systems and methods for dynamic user profile projection are provided. One or more aspects of the systems and methods includes computing, by a prediction component, a predicted number of lookups for a future time period based on a lookup history of a user profile using a lookup prediction model; comparing, by the prediction component, the predicted number of lookups to a lookup threshold; and transmitting, by a projection component, the user profile to an edge server based on the comparison.

Abstract: Embodiments of the present disclosure are directed to a system, methods, and computer-readable media for generating a hybrid data model. In embodiments, data feeds having different identities are used to generate profile fragments in one environment while relationships between the different identities are discerned in a separate environment. When a query is executed, an identity-based graph is generated to create a snapshot of the relationships determined at that time. Using the identity-based graph, those identities having a relationship to one another and to the query are determined. Profile fragments that correspond to the query-related identities are then aggregated together into a single hybrid data model.