Methods, apparatus, systems and articles of manufacture to expand panelist enrollment are disclosed. An example apparatus includes a network communicator to enable the apparatus to communicate with a local area network. A media monitor is to monitor a media presentation of the apparatus and report monitoring data identifying the media presentation to a central facility. A network scanner is to scan the local area network and store an identification of a second device connected to the same local area network as the apparatus. A network information processor is to review the identification of the second device connected to the same local area network as the apparatus, the network information processor to add the identification of the second device to a fingerprint if the second device is commonly connected to the same local area network as the apparatus. A fingerprint reporter is to transmit the fingerprint to the central facility.

Building and controlling access to a detailed profile of a consumer, including: generating the detailed profile of the consumer using a blockchain-based media ledger; enabling the consumer to subscribe to an advertisement network to control the access to the detailed profile of the consumer; recording consumptions and transactions of the consumer in the advertisement network as a media consumption history of the consumer; and ingesting the media consumption history into the blockchain-based media ledger. Keywords include blockchain, advertising, cryptographic token, and customer data.

Methods, computer-readable media, systems, and/or apparatuses are provided for providing offer and insight generation functions. User input requesting an offer or insight may be received and an image of a photographic identification of a user may be requested. The image of the photographic identification may be captured and stored. A self-captured image of the user may be captured (e.g., via an image capture device of the computing device) and compared to an image of a user from the photographic identification. Responsive to determining that the images match, displaying an instruction to capture a vehicle identification number. The vehicle identification number may be captured. Data, including location data, may be extracted and an archive including the extracted data may be generated and the data may be transmitted to an entity computing system for processing. The entity computing system may evaluate the data and generate one or more insights and/or outputs.

Illustrative methods and systems may determine whether a rideshare is verified based on received rideshare data. A verification code may be assigned to a rideshare trip. The verification code may be provided to a rider of the rideshare trip. The verification code may be received by a vehicle device assigned to the rideshare trip via user input or communication from the rider device. Whether the rider has entered the correct vehicle for the rideshare trip may be verified based on the verification code assigned to the rideshare trip and the verification code received by the rideshare vehicle.

Systems and methods are disclosed for associating a plurality of Internet-enabled devices with a common user profile for targeting Internet content or advertising. One method includes: receiving, from a plurality of Internet-enabled devices, a plurality of requests for electronic content or advertising; extracting, from each of the plurality of requests, a source IP address and a unique identifier associated with the respective Internet-enabled device; identifying each possible pair of devices from which requests were received; calculating for each possible pair of devices a probability that the pair of devices are owned or operated by a common user; and prompting a user to either confirm a characteristic of a prior browsing session or to log-in to an account associated with the common user based on a comparison of the calculated probability to one or more thresholds.

A method includes training a plurality of different types of machine learning models using a training dataset to produce a set of trained machine learning models and determining a lift of each trained machine learning model in the set of trained machine learning models using a validation dataset. The method also includes selecting a trained machine learning model from the set of trained machine learning models that has a highest lift of the set of trained machine learning models and predicting a likelihood that a person will perform an action by applying the selected trained machine learning model to data about the person.

Systems and methods directed to managing computer resource allocation by monitoring signals indicating demand for services utilizing computer resources are described. A method includes maintaining, for each first event of first events, historical registration data and respective parameter values of the first event and identifying, for a second event having an open registration status, respective parameter values of the second event, and registration data for the second event. The method includes computing a similarity score between the second event and each first event of the plurality of first events, based on the respective parameter values of the first event and the second event and the registration data of the second event and the historical registration data of the first event, generating, for the second event, a projected number of entities based on determined information and determining a ranking of the second event.

In one example, a method includes generating, responsive to receiving a request for a recommendation for a group of users and based on first privacy level data for users of the group, an original list of recommendations for the group. In this example, the method further includes evaluating, by respective computational assistants associated with the users of the group and based on respective second privacy level data for the users of the group, recommendations from the original list of recommendations for inclusion in a pruned list of recommendations for the group, wherein the second privacy level is more restricted than the first privacy level. In this example, the method further includes, in response to the pruned list of recommendations including at least one recommendation, outputting, for presentation to the users of the group, the pruned list of recommendations.

A content display system according to the present invention includes a content output unit configured to output content from a display medium and a detecting unit configured to detect a status of a preset target. Then, the content output unit is configured to, in a case where the status of the target satisfies a preset switching condition, perform a switching process to switch the content output from the display medium to other content, and furthermore, in a case of performing a plurality of switching processes, perform at least switching processes for which different switching conditions are set.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining and recommending the types of digital components that content providers can generate and provide for distribution to client devices. In one aspect, a method can determine whether a content provider has not previously provided a first digital component of a first media type. A first set of user interaction data can be obtained and input into a machine learning model. The model can can output result data for expected affirmative user actions related to the first digital component of the first media type. Based on the result data, a recommendation specifying whether the content provider should provide the first digital component of the first media type can be generated and provided to the content provider.