A system for, and method of, generating textual outputs based on descriptor classifications, including a computing device configured to receive a specified location and a nourishment intake theme from a remote device, generate, as a function of a group machine-learning model, a user group theme for the first remote device, identify at least a food provider located within the specified location, determine, as a function of an descriptor machine-learning model, a descriptor classification for the first remote device and generate at least an user interface element at the first remote device as a function of the descriptor classification.

A wearable device and a method for providing a widget thereof are provided. A method for providing a widget in a wearable device of the present disclosure comprises the steps of: sensing status information of a user; transmitting the status information of the user to an external server; selecting an application type to be provided from the external server according to a user command; receiving, from the external server, information on at least one application corresponding to the status information of the user on the basis of the selected application type and the status information of the user; and providing, on a screen, a widget corresponding to an application selected by the user among the at least one application.

A method of providing targeted content across user channels includes receiving a plurality of device activity events on a user device, storing the received plurality of device activity events, creating an audience population based on the stored device activity events, determining links for additional secondary user devices based on the user device, creating a cross-channel advertising campaign targeting the determined audience population, and running the cross-channel advertising campaign based on the device activity and the determined additional secondary user devices.

Embodiments include apparatuses, methods, and systems for segmenting a target region for a target user based on payment transactions within a payment processing system. The embodiments include identifying a target user from users based on payment transaction data, and determining target regions for the target user based on the payment transaction data of the target user and users. The target user may have a propensity for initiating transaction activity in the target regions within a predetermined time period. The embodiments include generating propensity scores for the target regions based on the payment transaction data, identifying a target region for the target user based on the propensity scores, and transmitting merchant offers to the target user based on the identified target region. The propensity scores may be ranked into a list of target region rankings, where the target region is a maximum score in the list of target region rankings.

User selections entered in the media application or any user input device behavior with user devices may be recorded as clickstream data. The clickstream data may be used to deduce information about the user or a media item being consumed. A user may be profiled based on his or her input device behavior using a plurality of time-stamped indicators. A degree of user interest may be determined based on a time period between the time-stamped indicators, the number of time-stamped indicators within a period of time, and/or a type of user action.

Systems and methods are described to provide additional relevant content to a viewer of digital media such as a webpage. A webpage being viewed is divided into regions and in each region, statistics are compiled on pertinent words and phrases. Statistically significant words and phrases are compared with semantically similar words and phrases in the additional content. Where there is a significant match between the viewed content and available additional content, the additional content is provided to the user.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and cause the one or more processors to perform tracking, using the one or more processors, usage history of a user; creating training data from the usage history of the user; training a predictive algorithm on the training data; for each respective promotion in a plurality of promotions: assigning a respective weight to the respective promotion of the plurality of promotions by using the predictive algorithm, as trained; after a predetermined time period has elapsed, updating the usage history of the user; re-training the predictive algorithm, as trained, on the usage history of the user, as updated; for each respective promotion in the plurality of promotions: assigning a new respective weight to the respective promotion of the plurality of promotions using the predictive algorithm, as trained and re-trained; and coordinating displaying at least one respective promotion from the plurality of promotions based on the new respective weight, as assigned, for the at least one respective promotion. Other embodiments are disclosed herein.

Embodiments of the present disclosure include a platform for a resource provisioning system. The platform can execute big data analysis techniques to access-right data to generate statistics that characterize a set of users. For example, characteristics of users who access resources events can be analyzed with varying levels of detail. The access-right data can include access right assignments, and data identifying the users to which access rights are assigned. In some implementations, spatial management systems can access the platform to generate statistics for the resources.

A system and method of generating directed advertisements is disclosed herein. A computing system identifies a baseline history of customer spending for one or more merchant category codes. The computing system generates a time series algorithm for each merchant category code of the one or more merchant category codes. The time series algorithm is based on the baseline history. The computing system receives a stream of transactions associated with a user. The computing system inputs the stream of user data into the time series algorithm. The computing system receives, as output, an anticipated purchase window for the user with respect to each merchant category code of the one or more merchant category codes. The anticipated purchase window includes an anticipated date of next purchase and anticipated purchase amount. The computing system directs advertisements to the user in accordance with each respective anticipated purchase window.

A method and system for managing digital media campaigns accesses a set of programming data that contains various attributes of media assets that a media service provider will present to users. A media advertising campaign manager receives various criteria for the inclusion of advertisements in a particular entity's advertising campaign. The system uses the attributes in the data set to develop an advertising campaign that satisfies the entity's criteria. In various embodiments, the method system may consider the entity's preferences, seller criteria, and campaign requests for other entities.