Techniques are disclosed for implementing digital traffic data for analysis. In some examples, a telecommunications network determines an identity of a user associated with a user device that communicates with the telecommunications network. The telecommunications network identifies a physical location of the user device based on the user device communicating with a first transceiver of the telecommunications network. Then, the telecommunications network determines that the physical location of the user device corresponds to a first commercial location, and stores an indication that the user has visited the first commercial location.

Location history data can be used to identify attributes for a known geographic location of a business listing record for a business. As an example, location history data is received from each of a plurality of client computing devices. For each device, the location history data identifies an arrival and departure times for the known geographic location as well as prior and next visit information. The location history data is used as input into a classifier in order to identify a set of attributes for the geographic location and corresponding likelihood values for each of the attributes of the set of attributes. A subset of the set of attributes is determined such that the attributes describe aspects of the known geographic location based on the likelihood values. This subset is provided to a client computing device in response to a request for information about the geographic location.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.

A method of implementing sub-table replication starts with the processor detecting a first update to an entitlements table. The processor filters of a data table based on the first update. The processor then detects a second update to the entitlements table and performs incremental replication of the data table by causing a full inventory replication at a next refresh to be executed for provider accounts associated with the provider account identifiers in the entitlements table. Other embodiments are also described herein.

A system including one or more memory devices having instructions thereon, that, when executed by one or more processors, cause the one or more processors to receive a request from a service provider to be added to a trusted network of service providers, receive health safety data of a health data stream associated with the service provider and risk data of a risk data stream indicating risk levels associated with the service provider, determine that the service provider meets a level of heath safety by correlating the health safety data of the health data stream with the risk data of the risk data stream, receive a request from a device for a service provider recommendation of the trusted network of service providers, and provide an indication of the service provider to the device in response to a reception of the request for the service provider recommendation.

An example apparatus disclosed herein includes a data input interface to access different sets of initial adjustment factors, the initial adjustment factors generated to correct at least one of misattribution or non-coverage of media impressions logged by a database proprietor, a grouping controller to identify a first set of the initial adjustment factors as a set of donor adjustment factors based on (a) first audience members associated with the set of donor adjustment factors satisfying a first threshold and (b) first impressions associated with the first audience members satisfying a second threshold, and identify a second set of the initial adjustment factors as a set of recipient adjustment factors, and an imputation factor generator to generate imputation factors to correct ones of the recipient adjustment factors based on ones of the donor adjustment factors.

Methods, apparatus, systems and articles of manufacture are disclosed to generate computer-trained machine learning models to correct computer-generated errors in audience data. An example apparatus includes a query selector to select a plurality of features and a range of hyperparameters; a query generator to generate a plurality of machine learning models based on the plurality of features and the range of hyperparameters, and initiate training of the plurality of machine learning models based on demographic data in a privacy-protected cloud environment, the demographic data obtained from database proprietor user accounts corresponding to audience measurement panelists; and a model selector to select a first machine learning model from the plurality of machine learning models.

Methods and apparatus to generate audience metrics using third-party privacy-protected cloud environments. An example apparatus includes a data modifier to obtain a first matrix, the first matrix including first data indicative of entities and embeddings, the entities representative of at least one of search result clicks or videos watched, the embeddings representative of at least one of first classifications of the search result clicks or second classifications of the videos watched, generate a second matrix by reducing the first data in the first matrix to second data that satisfies a size corresponding to an input feature, and store the second matrix in first memory as the input feature, and a model generator to generate a demographic correction model based on the second matrix as the input feature, the demographic correction model to correct demographics corresponding to impressions logged in second memory.

Methods, apparatus, systems, and articles of manufacture are disclosed to adjust demographic information of user accounts to reflect primary users of the user accounts. An apparatus comprising: memory; and processor circuitry to execute instructions that causes the processor circuitry to at least: determine a first total score for a first panelist associated with a panelist user account based on at least one of a first impression score, a first age score, or a first gender score; determine a second total score for a second panelist associated with the panelist user account based on at least one of a second impression score, a second age score, or a second gender score; and in response to determining that the first total score satisfies a threshold, store demographics of the first panelist for the panelist user account.

An example apparatus disclosed herein includes a panelist detector to identify audience measurement panelists associated with database proprietor accounts, a sign-in rate calculator to determine an actual sign-in rate of the audience measurement panelists based on first impressions represented in database proprietor impressions data and second impressions represented in panel data, an adjustment factor generator to determine a first audience adjustment factor corresponding to a first sign-in rate and a second audience adjustment factor corresponding to a second sign-in rate, and a weighting controller to generate a first weighted audience adjustment factor and a second weighted audience adjustment factor by weighting the first and second audience adjustment factors by the actual sign-in rate, the adjustment factor generator to determine a signed-out adjustment factor based on the first and second weighted audience adjustment factors.