A method of providing a content stream based on capturing an initial delivery of the content stream. The method comprises obtaining manifest data related to the initial delivery of the content stream, the manifest data being obtained one or more times in a sequence during the initial delivery of the content stream to generate one or more manifest files; associating a time-stamp with each of the manifest files, the time stamp being indicative of a time of obtaining the associated manifest file; processing each of the manifest files to identify one or more addresses referenced in the manifest file of one or more segments comprising a portion of the content stream in the initial delivery; accessing one or more of the segments identified via the one or more addresses referenced in the manifest files; modifying a last one of the manifest files to include at least a portion of an earlier manifest file of the manifest files; and providing a client with access to the manifest files including the modified last manifest file and the accessed one or more segments, thereby enabling the client to receive at least a portion of the content stream.

Aspects of the subject disclosure may include, for example, a method, including identifying recommended video clips for a user of a communication device according to a video viewing profile for the user and video subject matter information associated with a plurality of video clips, identifying an edge cloud server for facilitating network access by the communication device at a location, determining a reduced activity period for a data path between a video content server and the edge cloud server by comparing activity information for the data path and an activity threshold, directing the video content server to store the recommended video clips at the edge cloud server during the reduced activity period, and providing a listing of the recommended video clips to an application, where the communication device receives a video clip of the recommended video clips from the edge cloud server responsive to a selection of the video clip via the application. Other embodiments are disclosed.

Embodiments herein describe a content distribution system that removes time-dependent promotional content before providing a recording of a media presentation (e.g., show or program) to a video-on-demand (VOD) provider. To receive Nielsen credit for a subscriber watching a recording of the media presentation using VOD, the recording must be almost the same as the live version of the media presentation which includes the original program content and the commercial advertisements shown during commercial breaks. However, some shows also include promotional content that a telecommunication or cable provider adds to the media presentation to promote other shows or events being broadcasted later. By the time the user views the recording, however, the promotional content may already be outdated. The embodiments herein describe techniques for removing time-dependent promotional content from a media presentation before the recording of the media presentation is sent to VOD providers.

Aspects of the subject disclosure may include, for example, facilitating access to a synopsis of a missed portion of a media program, identifying subject matter in a segment of content in the media program that has not been presented, determining a particular time for presenting the summary according to the subject matter in the segment of content, and initiating a presentation of the summary at the particular time. Other embodiments are disclosed.

A system and method are disclosed that, in an embodiment, are related to goal-oriented generation of advertising spot sets. The system and method each involve: receiving spot inventory data associated with a plurality of TV stations; receiving a rule variable associated with an advertising rule; receiving a goal variable associated with a goal; applying the advertising rule to select a plurality of spots that are eligible to form one or more spot sets; forming or generating at least one of the spot sets depending, at least in part, on a proximity to the goal; and generating an output associated with the generated spot set.

A method and system for planning and running video-on-demand (VOD) advertising includes a planner for planning advertising campaigns and an ad selector for running selected advertisements from selected ones of the campaigns. The campaigns are associated with household demographic classifications, video content category categories, household geographic locations, and/or video viewing times. In response to a viewer requesting a video, the selector selects the campaigns corresponding to the demographic classification associated with the viewer, the content category of the requested video, the geographic location associated with the viewer, and/or the viewing time at which the requested video is viewed. The demographic classification is determined by using an identifier of the viewer's set-top-box. The selector may select the campaigns corresponding to the content categories of the requested video. The content categories are determined by using an identifier associated with the requested video.

Systems, methods and articles for optimizing the clearance of content, such as advertisements. The systems disclosed herein provide a greater chance that offers to buy advertisement placement opportunities from media providers are accepted by the media providers. This is achieved by matching advertisements to advertisement placement opportunities which match buyer goals and provider goals, and by using historical data related to advertisements that the seller has cleared. The system may optimize clearance for multiple buyers which are competing for the same advertisement placement opportunities at the same time.

Devices, systems, and methods are provided for on-target rate optimization for video. A method may include receiving streaming video advertisement impression data; receiving user activity data indicative of day-parts when viewers watch content; generating, based on the streaming video advertisement impression data and the survey data, using a machine learning model, a demographic probability vector, wherein each entry of the demographic probability vector is indicative of a probability that a viewer is in a respective age range of the non-overlapping demographic groups; generating, using the machine learning model, an audience recognition model with the demographic probability vector; generating a synthetic audience model predicting future advertisement viewing behavior; generating an assignment of an advertisement bid to a respective demographic group of the non-overlapping demographic groups; and generating, based on the assignment, a list of target demographic groups of the non-overlapping demographic groups for a bid request associated with the advertisement bid.

A hardware media items scheduling and packaging system, which schedules and distributes channels to be viewed on a plurality of consumer devices, extracts contextual data from program-specific information associated with programming media content of a channel received from a distribution source device. A plurality of potential non-programming media items is determined for a plurality of users based on a match between a sentiment type of each of a plurality of non-programming media items and the extracted contextual data. Based on at least the extracted contextual data and the sentiment type of each of the plurality of potential non-programming media items, a plurality of candidate spots in the programming media content is determined. Based on at least a set of constraints and user estimation data associated with the plurality of users, a schedule of non-programming media item(s) is dynamically generated for at least one candidate spot in the programming media content.

Data on a user interacting with a media presentation is collected at a client device. The data includes facial image data of the user. The facial image data is analyzed to extract cognitive state content of the user. One or more emotional intensity metrics are generated. The metrics are based on the cognitive state content. The media presentation is manipulated, based on the emotional intensity metrics and the cognitive state content. An engagement score for the media presentation is provided. The engagement score is based on the emotional intensity metric. A facial expression metric and a cognitive state metric are generated for the user. The manipulating includes optimization of the previously viewed media presentation. The optimization changes various aspects of the media presentation, including the length of different portions of the media presentation, the overall length of the media presentation, character selection, music selection, advertisement placement, and brand reveal time.