Abstract: Systems and methods are described for identifying a target entity that a user intends to refer to based on input that may include only a partial name of the entity. A system may receive a user's entity search query, which may include a partial entity name, then may determine initial candidate matching entities and associated name match scores for each of the initial candidate matching entities relative to the input string, such as using string matching or fuzzy matching techniques. The system may apply a probability match model to generate an overall match score for individual ones of the initial candidate matching entities, then may generate a response to the entity search query that includes information regarding one or more of the initial candidate matching entities with an overall match score exceeding a threshold.

Abstract: Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

Abstract: Embodiments of a risk assessment system is disclosed, where the risk assessment system can receive patient related data (for example, patient records) and social determinants of health data to generate a risk model to predict potential health outcomes, such as, for example readmission risk, with accompanying social determinants of health insight, which may include actionable insights and deployed systems that follow interventions. The risk model can be used to calculate a risk score for a patient based on patient records and social determinants of health data associated with the patient to predict potential negative health outcome for the patient proactively so that actions can be taken using social determinants of health insights to prevent that outcome.

Abstract: The present disclosure describes systems and methods for providing enhanced location analysis and consumer insights using mobile sightings data. An approximate geographic location is useful to mobile service providers and advertisers who wish to provide targeted content to consumers based on their location. The location analysis described herein provides more depth and detail about the detected geographic location of the consumer and also insights into business locations visited by the user of the device, consumer/market segments and patterns of behavior (for an individual consumer and/or for aggregated group of consumers), retail trends and patterns, and other profile information. For example, a location profile analytics system as described herein can determine a probability that an approximate geographic location actually corresponds to a specific geographic location, such as a business location.

Abstract: Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

Abstract: The present disclosure describes systems and methods for providing enhanced location analysis and consumer insights using mobile sightings data. An approximate geographic location is useful to mobile service providers and advertisers who wish to provide targeted content to consumers based on their location. The location analysis described herein provides more depth and detail about the detected geographic location of the consumer and also insights into business locations visited by the user of the device, consumer/market segments and patterns of behavior (for an individual consumer and/or for aggregated group of consumers), retail trends and patterns, and other profile information. For example, a location profile analytics system as described herein can determine a probability that an approximate geographic location actually corresponds to a specific geographic location, such as a business location.

Abstract: Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

Abstract: Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

Abstract: The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g.

Abstract: The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g.

Abstract: The present disclosure describes systems and methods for automatically rolling-up data associated with one or more geographic units, such as ZIP+4 codes, such that the rollup comprises a minimum number of households to protect anonymity and ensure compliance with privacy regulations, while preserving variance of the underlying data associated with the geographic regions. Data attributes may include demographic data, socio-economic data, lifestyle segmentation, psychographic data, behavioral data, credit data, and other data. The rollup process may involve identifying one or more geographic units with a number of households below a minimum or threshold amount, applying filters to find candidate geographic units for rollup, scoring candidate geographic units to select best pairings for rollup, and repeating until the rollup group has at least the minimum number of households. The process may make trades off between granularity (e.g.

Abstract: Features are described for efficiently and accurately provisioning content to a mobile device with limited user interaction. The features include storing a content identifier for a content element and a publication rule for the content element in a data storage device, the publication rule identifying a user to whom the content element can be provided. The features include receiving, from a mobile device, a message including the content identifier and an identifier of the mobile device. The features include querying a user data store based at least in part on the identifier to obtain user information associated with the mobile device. The features include determining that mobile device is eligible to receive the content element. The features include generating content for the mobile device based at least in part on the user information and the content element and causing display of the same via the mobile device.

Abstract: Features are described for efficiently and accurately identifying a user of an electronic device with limited user interaction. The features include receiving a mobile device identifier from the mobile device. The features include transmitting the mobile device identifier to a service provider associated with the mobile device. The features include receiving information identifying the user from the service provider. The features include identifying a set of candidates associated with at least a portion of the information. The features include generating a metric for the candidates included in the set of candidates. An individual metric indicates a degree of relatedness between a value for the user for the at least one data field and a value for a candidate for the at least one data field. The features include identifying the user as a specific candidate included in the set of candidates based on the metric corresponding to a threshold.

Abstract: A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

Abstract: A limit stop filter support apparatus for use in controlling fluidic currents and limiting movement of an actuator within a housing, such as in a data storage device. First and second filter retention members extend from a filter support base to confine opposing ends of a filter used to filter fluidic currents within the housing, and a cantilevered limit stop extends from the base to contactingly limit movement of an actuator moveable within the housing. The limit stop preferably comprises a spring member supporting a latch member, the latch member selectively confining the actuator in a parked position. The first and second retention members each preferably include a shroud surface adjacent an outer peripheral edge of a rotatable storage medium to direct the fluidic currents established by rotation of the medium.