Abstract: A method and apparatus of a device for generating one or more content briefs is described. In an exemplary embodiment, the device receives a strategy for generating the plurality of content briefs, wherein each of the plurality of content briefs is a structured document that is used to guide creation of content. In addition, the device may collect a collection of content and generate a plurality of content clusters using unsupervised machine learning to cluster the content collection with the received strategy. Furthermore, the device may generate the plurality of content briefs from the plurality of content clusters.

Abstract: Within an advertising buying platform, advertising buyers are able to direct advertising content to TV/OTT/VOD inventory that matches targeted market segments. The advertising buyers select from a list of available market segments, and the system pairs the market segments to an anonymous dataset of media consumers (using a database of hashed online IDs). The dataset of hashed online IDs is then mapped to external OEM IDs (such as from a Smart TV) via the functions of a hashed identity mapping method. This permits the advertiser to target advertising content to a population of TV viewers. Also described herein are methods of bidding on programmatic TV content.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: A method and apparatus of a device for generating one or more headlines is described. In an exemplary embodiment, the device receives a strategy for generating the plurality of headlines, wherein each of the plurality of content briefs is a structured document that is used to guide creation of content. In addition, the device may collect a collection of content and generate a plurality of content clusters using at least an unsupervised learning to cluster the content collection with the received strategy. Furthermore, the may summarizes each of to the plurality of content clusters to generate the plurality of headlines.

Abstract: A method and apparatus of a device for generating one or more content briefs is described. In an exemplary embodiment, the device receives a strategy for generating the plurality of content briefs, wherein each of the plurality of content briefs is a structured document that is used to guide creation of content. In addition, the device may collect a collection of content and generate a plurality of content clusters using at least an unsupervised learning to cluster the content collection with the received strategy. Furthermore, the may generate the plurality of content briefs from at least the plurality of content clusters.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content to consumers' TV's using a programmatic TV bidding model. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: Processor-based systems and/or methods of operation may generate queries and suggest legacy narrative content (e.g., video content, script content) for a narrative under development. An artificial neural network (ANN, e.g., autoencoder) is trained on pairs of video and text vectors to capture attributes or nuances beyond those typical of keyword searching. Query vector representations generated using an instance of the ANN may be matched against candidate vector representations, for instance generated using an instance of the ANN from legacy narratives. Such may query for missing video and/or text for a narrative under development. Matches may be returned, including scores or ranks. Feature vectors may be shared without jeopardizing source narrative content. Legacy source narrative content may remain secure behind a controlling entity's network security wall.

Abstract: The present invention is directed to statistical methods for measuring cross-screen efficacy as it relates to advertising. The improved statistical methods provide the ability for advertisers and advertising agencies to predict the behaviors of consumers based on their aggregated cross-screen behavior. The system creates a new output that includes optimized user segments and classifications. A second part of the output is improved measurement and prediction of future consumer behaviors based on the processed multisided data on cross-screen behavior.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.

Abstract: Various embodiments provide input to and facilitate various operations of media production. An automated script content generator uses recurrent artificial neural networks trained using machine learning on a corpus of stories or scripts to generate and suggest script content and indicates effects changes to the script would have of the scenes, characters, interactions and other entities of the script. An automated producer breaks down the script to automatically generate storyboards, calendars, schedules and budgets and provides this as input to the pre-production operation within a media production environment. The system also provides information to affect and facilitate the greenlighting operation and other operations in the media production environment in an iterative script review and revision process.

Abstract: In various embodiments, the system provides input to and facilitates various operations of media production. An automated script content generator uses recurrent artificial neural networks trained using machine learning on a corpus of stories or scripts to generate and suggest script content and indicates effects changes to the script would have of the scenes, characters, interactions and other entities of the script. An automated producer breaks down the script to automatically generate storyboards, calendars, schedules and budgets and provides this as input to the pre-production operation within a media production environment. The system also provides information to affect and facilitate the greenlighting operation and other operations in the media production environment in an iterative script review and revision process.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: The present invention is directed to statistical methods for measuring cross-screen efficacy as it relates to advertising. The improved statistical methods provide the ability for advertisers and advertising agencies to predict the behaviors of consumers based on their aggregated cross-screen behavior. The system creates a new output that includes optimized user segments and classifications. A second part of the output is improved measurement and prediction of future consumer behaviors based on the processed multi-sided data on cross-screen behavior.

Abstract: In various embodiments, the system provides input to and facilitates various operations of media production. An automated script content generator uses recurrent artificial neural networks trained using machine learning on a corpus of stories or scripts to generate and suggest script content and indicates effects changes to the script would have of the scenes, characters, interactions and other entities of the script. An automated producer breaks down the script to automatically generate storyboards, calendars, schedules and budgets and provides this as input to the pre-production operation within a media production environment. The system also provides information to affect and facilitate the greenlighting operation and other operations in the media production environment in an iterative script review and revision process.

Abstract: Various embodiments provide input to and facilitate various operations of media production. An automated script content generator uses recurrent artificial neural networks trained using machine learning on a corpus of stories or scripts to generate and suggest script content and indicates effects changes to the script would have of the scenes, characters, interactions and other entities of the script. An automated producer breaks down the script to automatically generate storyboards, calendars, schedules and budgets and provides this as input to the pre-production operation within a media production environment. The system also provides information to affect and facilitate the greenlighting operation and other operations in the media production environment in an iterative script review and revision process.

Abstract: The current invention relates to a computer-generated method for optimizing placement of advertising content to consumers' TV's using a programmatic TV bidding model. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

Abstract: Within an advertising buying platform, advertising buyers are able to direct advertising content to TV/OTT/VOD inventory that matches targeted market segments. The advertising buyers select from a list of available market segments, and the system pairs the market segments to an anonymous dataset of media consumers (using a database of hashed online IDs). The dataset of hashed online IDs is then mapped to external OEM IDs (such as from a Smart TV) via the functions of a hashed identity mapping method. This permits the advertiser to target advertising content to a population of TV viewers. Also described herein are methods of bidding on programmatic TV content.