An example apparatus includes processor circuitry to: access first input data from meters, the meters to monitor media devices associated with a plurality of panelists, the first input data including media source data and panel data; reduce a dimensionality of the first input data to generate second input data of reduced dimensionality relative to the first input data, the dimensionality of the first input data to be reduced based on a prior probability of an audience rating associated with the plurality of panelists and an approximation of a dependency of the audience rating on at least one of the media source data and the panel data; and decode the second input data of reduced dimensionality to output a probability model parameter for a multivariate probability model, the multivariate probability model having dimensions corresponding to the first input data, the multivariate probability model to label census data.

Systems and methods for determining whether and how to present digital animations in a user interface are disclosed. According to certain embodiments, the systems and methods may facilitate the identification of a set of products or services purchased by an individual, and the determination of a reward level associated with the set of products or services. The systems and methods may select a digital animation, from a set of digital animations that is predetermined based on a set of probabilities, corresponding to the reward level, and present the digital animation in a user interface.

An advertising effect prediction device includes: a construction unit that converts layout information of delivered manuscript into a graph structure through collation with a flow line of a user using a scheme related to a GNN, and performs machine learning using a feature quality of each node in the graph structure and delivery user attribute information as explanatory variables and a flag indicating presence or absence of a click of each delivery user based on delivery result as an objective variable to construct a prediction model for predicting click through rate of an individual user; and a prediction unit that converts the layout information into a graph structure using the same scheme based on target user attribute information and the delivered manuscript and inputs the feature quantity and the target user attribute information to a prediction model, to obtain click through rate prediction value of the individual user.

Systems and methods are presented for managing the cadence (e.g., frequency or rate) that electronic promotion correspondence is sent to a consumer. A system may access a target cadence indicator associated with a consumer that indicates of a target rate for sending electronic promotion correspondence to the consumer. The system may also determine an actual cadence indicator for the consumer over a predetermined period of time and analyze a potential electronic promotion correspondence for sending to the consumer. The system determines whether to send the electronic correspondence to the consumer based on the target cadence indicator, the actual cadence indicator, and the analysis of the electronic promotion correspondence.

The present invention relates to methods and systems for targeting and retargeting individuals with advertisement spots during television broadcasting. The method and system enable an advertiser for identifying and categorizing a set of viewers or individuals for retargeting advertisement based on parameters such as, but not limited to, interests or preferences of the individuals, past purchases and interactions of the individuals with the advertiser. The method and system further enable the advertiser to segregate the plurality of individuals into subgroups on the basis of information such as, but not limited to, demography, psychographic and behavioral characteristics of the plurality of individuals. The method and system then enable the advertiser to define one or more advertisement spots and corresponding advertisements to be delivered to different sub groups of individuals based on the categorization. Thereafter, the method and system retarget individuals by sending individualized messages in the one or more advertisement spots.

Methods and systems for presenting online content elements based on information known to a service provider. One of the methods is a method for presenting online content at a communication apparatus, the communication apparatus being assigned an identifier. The method comprises: obtaining information that pertains to a profile associated with the identifier and provided by a service provider involved in assigning the identifier to the communication apparatus; determining an online content element to be presented at the communication apparatus based on the information; and causing the communication apparatus to present the online content element. Another one of the methods is a method for facilitating determination of online content to be presented at a communication apparatus. Servers for implementing the methods are also provided.

An online system monitors actions performed by users of the online system in association with being presented with content items that are associated with various categories. A histogram may be generated to describe a pattern of an action previously performed by a user in response to being presented with content items associated with a category. The online system trains a model to predict a likelihood that the user will perform the action in response to being presented with a content item associated with the category based on the pattern of the action previously performed by the user and information describing one or more recent performances of the action by the user with a content item associated with the category. The predicted likelihood may be included in a content selection process that selects one or more content items for presentation to the user.

Systems and methods may reducing website redirection for surveys. A method may include receiving, at a host server, an indication via an application programming interface (API), the indication including a request for survey. Demographic questions may be supplied and at least one may be answered. The method may include determining whether a respondent to the demographic questions is qualified for a survey, and sending information including a result of the determination.

This disclosure generally covers systems and methods that determine demographic labels for a user or a group of users by using digital inputs within a predictive model for demographic classification. In particular, the disclosed systems and methods use a unique combination of classification algorithms to determine demographic labels for users as a potential audience of digital content items. When applying the combination of classification algorithms, the disclosed systems and methods use a first classification algorithm to determine user-level-latent features for each user within a group of users based on demographic-label statistics associated with particular digital content items. The disclosed systems and methods then use the user-level-latent features and session-level features (from sessions of each user consuming the digital content items) as inputs in a second classification algorithm to determine a demographic label for each user within the group of users.

In accordance with one or more aspects of the advertisement-controlled Web page customization discussed herein, functionality allowing an advertisement to set various presentation properties of a Web page is exposed. The advertisement invokes the functionality to set a particular presentation property of the Web page to a corresponding property value in order to customize the presentation of the Web page as desired by the advertisement.