Dynamically scheduling non-programming media items in contextually relevant programming media content

A method, comprising:

• in a media items scheduling and packaging system that schedules and distributes one or more channels for view on a plurality of consumer devices:
• receiving, by one or more circuits, programming media content of a channel of the one or more channels from a distribution source device via a network;
• storing at least one of phrases or keywords associated with semantics of the programming media content with corresponding contextual data;
• extracting, by the one or more circuits, contextual data from program-specific information associated with the programming media content based on a mapping of the contextual data and the stored at least one of phrases or keywords associated with semantics of the programming media content;
• determining, by the one or more circuits, a plurality of potential non-programming media items from a plurality of non-programming media items for a plurality of users, based on a match between a sentiment type of each of the plurality of non-programming media items and the extracted contextual data;
• determining, by the one or more circuits, a plurality of candidate spots in the programming media content based on at least the extracted contextual data and the sentiment type of each of the determined plurality of potential non-programming media items;
• and
• generating, by the one or more circuits, based on at least a set of constraints and user estimation data associated with the plurality of users, a schedule of at least one potential non-programming media item from the determined plurality of potential non-programming media items for at least one candidate spot from the determined plurality of candidate spots in the programming media content of the channel for view at the plurality of consumer devices.

A non-transitory computer-readable medium having stored thereon, computer executable instruction that when executed by a computer, causes the computer to execute operations, the operation comprising:

• in a media items scheduling and packaging system that schedules and distributes one or more channels for view on a plurality of consumer devices:
• receiving programming media content of a channel of the one or more channels from a distribution source device via a network;
• storing at least one of phrases or keywords associated with semantics of the programming media content with corresponding contextual data;
• extracting contextual data from program-specific information associated with the programming media content based on a mapping of the contextual data and the stored at least one of phrases or keywords associated with semantics of the programming media content;
• determining a plurality of potential non-programming media items from a plurality of non-programming media items for a plurality of users, based on a match between a sentiment type of each of the plurality of non-programming media items and the extracted contextual data;
• determining a plurality of candidate spots in the programming media content based on at least the extracted contextual data and the sentiment type of each of the determined plurality of potential non-programming media items;
• and
• dynamically generate, based on at least a set of constraints and user estimation data associated with the plurality of users, a schedule of at least one potential non-programming media item from the determined plurality of potential non-programming media items for at least one candidate spot from the determined plurality of candidate spots in the programming media content of the channel for view at the plurality of consumer devices.

A media items scheduling and packaging system, comprising:

• a scheduling system configured to:
• receive programming media content of a channel from a distribution source device via a network;
• store at least one of phrases or keywords associated with semantics of the programming media content with corresponding contextual data;
• extract contextual data from program-specific information associated with the programming media content based on a mapping of the contextual data and the stored at least one of phrases or keywords associated with semantics of the programming media content;
• determine a plurality of potential non-programming media items from a plurality of non-programming media items for a plurality of users, based on a match between a sentiment type of each of the plurality of non-programming media items and the extracted contextual data;
• determine a plurality of candidate spots in the programming media content based on at least the extracted contextual data and the sentiment type of each of the determined plurality of potential non-programming media items;
• and
• dynamically generate, based on at least a set of constraints and user estimation data associated with the plurality of users, a schedule of at least one potential non-programming media item from the determined plurality of potential non-programming media items for at least one candidate spot from the determined plurality of candidate spots in the programming media content of the channel for view at a plurality of consumer devices.