Abstract: Systems and methods are validating data in a data set. A data set including data to validate and a validator to use in validating the data is selected based on user input generated based on interactions of a user with a graphical user interface. The validator is applied to the data to determine whether one or more statistics generated through application of the validator to the data is valid or invalid based on a validation routine associated with the validator. A data quality report indicating whether the data set is valid or invalid, based on a determination of whether the one or more statistics is valid or invalid, is generated and selectively presented to the user through the graphical user interface.

Abstract: Systems and methods are disclosed for systems and user interfaces for rapid analysis of viewership information. One of the methods includes accessing databases storing viewership information associated with segments, with each segment being associated with common features of viewers. Measures of association between the segment and content items are maintained for each segment. An interactive user interface is presented via a user device, the interactive user interface enabling creation of a customized viewing audience. The interactive user interface receives user input indicating a segment, identifies similar segments based on associations between features of the segment and of other segments, and presents the identified segments. Analysis information associated with the segments is presented for at least one of the one or more segments, with the segments being included in the customized viewing audience.

Abstract: Systems and methods are provided for identifying relevant information for an entity, referred to as a seed entity. A plurality of search queries can be generated each comprising a property of a seed entity or one of the entities associated with the seed entity (seed-linked entities). Preferably, a collection of search queries includes ones representing different properties of the seed entity and properties of different seed-linked entities. Optionally, the collection of search queries is optimized to reduce search burden. Searches can then be conducted with the search queries in one or more data sources to obtain a plurality of search results, wherein each search result comprises a hit entity and one or more entities associated with the hit entity (hit-linked entity).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a feature clustering of users, user correlation database access, and user interface generation system. The system can obtain information stored in different databases located across geographic regions, and determine unique users from the different information. The information can be included in unique records in the databases, with each record describing a particular user, and with each user described with imperfect identifying information. The system can analyze the different information utilizing machine learning models, and can associate each record with a particular unique user. The system can obtain identifications of items associated with each user, and determine the propensity of the user to disassociate with one or more items, or determine likelihoods of future association with different items not presently associated with the user.

Abstract: Systems and methods are provided for investigation of network activities. Network activity information may be accessed. The network activity information may describe for an individual (1) respective relationship with one or more persons; and (2) respective activity status information indicating whether a given person has engaged in a particular activity. A network activity graph may be generated based on the network activity information. The network activity graph may include two or more nodes representing the individual and the one or more persons. Connections between the nodes may represent the respective relationships between the individual and the one or more persons. Data corresponding to the network activity graph may be presented through an interface.

Abstract: Systems and methods are validating data in a data set. A data set including data to validate and a validator to use in validating the data is selected based on user input generated based on interactions of a user with a graphical user interface. The validator is applied to the data to determine whether one or more statistics generated through application of the validator to the data is valid or invalid based on a validation routine associated with the validator. A data quality report indicating whether the data set is valid or invalid, based on a determination of whether the one or more statistics is valid or invalid, is generated and selectively presented to the user through the graphical user interface.

Abstract: Systems, methods, and non-transitory computer readable media are provided for labeling depictions of objects within images. An image may be obtained. The image may include a depiction of an object. A user's marking of a set of dots within the image may be received. The set of dots may include one or more dots. The set of dots may be positioned within or near the depiction of the object. The depiction of the object within the image may be labeled based on the set of dots.

Abstract: Systems and methods are validating data in a data set. A data set including data to validate and a validator to use in validating the data is selected based on user input generated based on interactions of a user with a graphical user interface. The validator is applied to the data to determine whether one or more statistics generated through application of the validator to the data is valid or invalid based on a validation routine associated with the validator. A data quality report indicating whether the data set is valid or invalid, based on a determination of whether the one or more statistics is valid or invalid, is generated and selectively presented to the user through the graphical user interface.

Abstract: Systems, methods, and non-transitory computer readable media are provided for labeling depictions of objects within images. An image may be obtained. The image may include a depiction of an object. A user's marking of a set of dots within the image may be received. The set of dots may include one or more dots. The set of dots may be positioned within or near the depiction of the object. The depiction of the object within the image may be labeled based on the set of dots.

Abstract: Systems and methods are provided for identifying and compiling information relating to an entity for investigative analysis. The system may comprise one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to search, in one or more data sources, with a plurality of known characteristics of an entity to obtain a first plurality of records, identify from the first plurality of records a subset of records that match the known characteristics with a substantial confidence, compile the subset of records to form a unified record representing the entity and conduct a second search with information from the unified record to obtain a second plurality of search results.

Abstract: Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.

Abstract: Systems and methods are provided for identifying and compiling information relating to an entity for investigative analysis. The system may comprise one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to search, in one or more data sources, with a plurality of known characteristics of an entity to obtain a first plurality of records, identify from the first plurality of records a subset of records that match the known characteristics with a substantial confidence, compile the subset of records to form a unified record representing the entity and conduct a second search with information from the unified record to obtain a second plurality of search results.

Abstract: Systems and methods are provided for identifying relevant information for an entity, referred to as a seed entity. A plurality of search queries can be generated each comprising a property of a seed entity or one of the entities associated with the seed entity (seed-linked entities). Preferably, a collection of search queries includes ones representing different properties of the seed entity and properties of different seed-linked entities. Optionally, the collection of search queries is optimized to reduce search burden. Searches can then be conducted with the search queries in one or more data sources to obtain a plurality of search results, wherein each search result comprises a hit entity and one or more entities associated with the hit entity (hit-linked entity).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a feature clustering of users, user correlation database access, and user interface generation system. The system can obtain information stored in different databases located across geographic regions, and determine unique users from the different information. The information can be included in unique records in the databases, with each record describing a particular user, and with each user described with imperfect identifying information. The system can analyze the different information utilizing machine learning models, and can associate each record with a particular unique user. The system can obtain identifications of items associated with each user, and determine the propensity of the user to disassociate with one or more items, or determine likelihoods of future association with different items not presently associated with the user.

Abstract: Systems and methods are provided for identifying relevant information for an entity, referred to as a seed entity. A plurality of search queries can be generated each comprising a property of a seed entity or one of the entities associated with the seed entity (seed-linked entities). Preferably, a collection of search queries includes ones representing different properties of the seed entity and properties of different seed-linked entities. Optionally, the collection of search queries is optimized to reduce search burden. Searches can then be conducted with the search queries in one or more data sources to obtain a plurality of search results, wherein each search result comprises a hit entity and one or more entities associated with the hit entity (hit-linked entity).

Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a feature clustering of users, user correlation database access, and user interface generation system. The system can obtain information stored in different databases located across geographic regions, and determine unique users from the different information. The information can be included in unique records in the databases, with each record describing a particular user, and with each user described with imperfect identifying information. The system can analyze the different information utilizing machine learning models, and can associate each record with a particular unique user. The system can obtain identifications of items associated with each user, and determine the propensity of the user to disassociate with one or more items, or determine likelihoods of future association with different items not presently associated with the user.

Abstract: Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.

Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.

Abstract: Systems and methods are provided for identifying relevant information for an entity, referred to as a seed entity. A plurality of search queries can be generated each comprising a property of a seed entity or one of the entities associated with the seed entity (seed-linked entities). Preferably, a collection of search queries includes ones representing different properties of the seed entity and properties of different seed-linked entities. Optionally, the collection of search queries is optimized to reduce search burden. Searches can then be conducted with the search queries in one or more data sources to obtain a plurality of search results, wherein each search result comprises a hit entity and one or more entities associated with the hit entity (hit-linked entity).