Aspects of the subject disclosure may include, for example, collecting television viewership information for viewers of television content items of a television advertising campaign, collecting digital viewership information for online activity by users, joining the television viewership information and the digital viewership information, wherein the joining comprises associating household identifiers of the television viewership information with device identifiers of the digital viewership information, building a content ranking of digital content items closest to the television content items and initiating, by the processing system, a digital advertising campaign with one or more digital content items of the content ranking of digital content items attached to the digital advertising campaign. Other embodiments are disclosed.

A method includes determining, by a computing system, a probability of whether at least a threshold portion of a particular advertisement will be presented on a particular content presentation device, and a cost associated with presentation of the particular advertisement on the particular content presentation device. The computing system calculates an expected revenue associated with presentation of the particular advertisement based on the probability and the cost. When the expected revenue exceeds a threshold revenue, the computing system communicates the particular advertisement to the particular content presentation device.

A method includes accessing video data that includes at least two different modalities. The method also includes using a convolutional neural network layer to incorporate temporal coherence into a machine learning model architecture configured to process the video data. The method further includes learning dependency among the at least two different modalities in an attention space of the machine learning model architecture. In addition, the method includes predicting one or more correlations among the at least two different modalities.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: tracking touchpoints by a user over a first time period; after receiving an order, determining, using a machine-learning model, a respective contribution of each of the touchpoints, wherein the machine-learning model is trained to predict a probability of the user placing the order during a second time period based on an input feature vector representing a set of touchpoints; and allocating a respective percentage of credit for the order to the each of the touchpoints based on the respective contributions of the each of the touchpoints. Other embodiments are disclosed.

The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems. A system and method for providing reporting-related services to client entities. These services may determine a set of reportable properties based on a type of chart and at least one data source selected by a user. A report plan may be executed on a knowledge graph to obtain a reporting dataset. A custom chart may be generated based on the type of chart selected, the reporting dataset, and a set of reporting parameters.

The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems. A system and method for providing payment-related services that may utilize checkout parameters, a link generation service, a payment processing service, and a post-payment service. The link generation service may serve a checkout page using a set of the checkout parameters. The payment processing service may receive a transaction notification indicating whether a payment was successful or unsuccessful. The post-payment service may initiate a post-transaction workflow corresponding to an outcome indicated by the transaction notification.

The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems. A system and method for maintaining unified events such as maintaining an ontology data store and an event datastore. The event datastore may store event record instances of one or more different types of event records. The system and method may identify one or more types of event records that track a specific event type based on a specific event type of a new event instance.

The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems. A system and method for providing conversation intelligence services may include pre-processing, transcribing, and post-processing. A conversation recording may be pre-processed generating a conversation record (e.g., conversation object). The pre-processed conversation recording may be transcribed into a transcript. The transcript may be post-processed which may include keyword extraction, topic extraction, feature extraction, event generation, trigger action, and/or search indexing. Conversation information may be presented based on the pre-processing, the transcribing, and the post-processing.

A disclosed example apparatus includes a communication interface to: access impression count data corresponding to a plurality of platforms; and access deduplicated total audience size data; an arithmetic logic unit to: generate a total impressions count by aggregating the impression count data corresponding to the plurality of platforms; generate an estimated per-platform impression count by dividing the total impressions count by a number of the platforms, a solver controller to: instruct a numerical solver to utilize the number of the platforms, the deduplicated total audience size data, and the estimated per-platform impression count to estimate the deduplicated audience size of a first platform of the platforms; and store the deduplicated audience size of the first platform in memory.

A method includes determining, by a computing system, a probability of whether at least a threshold portion of a particular advertisement will be presented on a particular content presentation device, and a cost associated with presentation of the particular advertisement on the particular content presentation device. The computing system calculates an expected revenue associated with presentation of the particular advertisement based on the probability and the cost. When the expected revenue exceeds a threshold revenue, the computing system communicates the particular advertisement to the particular content presentation device.