A method of assigning advertisements to slots in video channels of a bundle of channels provided to an end user. The method includes managing credits, for each specific channel of the channels, indicative of a difference between a number of advertisements provided by an owner of the specific channel that were displayed on other channels and a number of advertisements provided by owners of other channels displayed on the specific channel In addition, scores indicative of a predicted success of the advertisement with the end user are calculated for a plurality of advertisements. An advertisement to be displayed to the end user is selected responsive to a function of both the calculated scores and the managed credits.

Methods, apparatuses, systems, and software are described for providing content to a device comprising streaming content and sending content in a non-streaming manner (e.g., by downloading a file containing the content). In some aspects, switching between streaming and downloading may be performed in a dynamic manner during presentation of the content, and may be seamless to the user's viewing experience.

Methods, devices, and non-transitory computer-readable storage mediums are provided for distributing red envelops. The method includes following steps: generating red envelopes based on a user instruction; receiving a first request for accessing the red envelopes in response to a delay condition being fulfilled; calculating one or more amounts based on an audience number of online audiences at current moment; and placing the one or more amounts at a preset position of a container for displaying.

Techniques are described for machine learning-based generation of target segments is leveraged in a digital medium environment. A segment targeting system generates training data to train a machine learning model to predict strength of correlation between a set of users and a defined demographic. Further, a machine learning model is trained with visit statistics for the users to predict the likelihood that the users will visit a particular digital content platform. Those users with the highest predicted correlation with the defined demographic and the highest likelihood to visit the digital content platform can be selected and placed within a target segment, and digital content targeted to the defined demographic can be delivered to users in the target segment.

A computer-implemented method for selecting efficient encoders for streaming media may include (i) predicting that an expected download demand for a higher-demand segment of a media file is higher than an expected download demand for a lower-demand segment, (ii) encoding each segment of the media file with an encoder that correlates to the expected download demand of the segment by (a) encoding the higher-demand segment with a more computationally intensive encoder that produces a more efficiently compressed segment compared to a less computationally intensive encoder that produces a less efficiently compressed segment and (b) encoding the lower-demand segment with the less computationally intensive encoder, and (iii) enabling streaming of the media file by providing the more efficiently compressed encoding of the higher-demand segment and the less efficiently compressed encoding of the lower-demand segment. Various other methods, systems, and computer-readable media are also disclosed.

A computer-implemented method for preserving video stream quality may include (i) identifying a plurality of video streams being transmitted via a shared connection with limited bandwidth, (ii) determining that viewership of a video stream within the plurality of video streams falls below a popularity threshold, (iii) increasing bandwidth availability for a remainder of the plurality of video streams by ceasing transmission of the video stream with the viewership that falls below the popularity threshold, and (iv) continuing to transmit the remainder of the plurality of video streams via the shared connection with the limited bandwidth. Various other methods, systems, and computer-readable media are also disclosed.

A system and method for content aware monitoring of an output of a media channel by a media system is provided herein. In at least one embodiment, the method comprises: receiving a media assertion schedule comprising a schedule of assertion checks which allow validating that the output of the media channel, by the media system, is synchronized with an expected media channel output; receiving, from a signature generating module, at least one observed signature file; determining that the timestamp data, in each of the at least one received observed signature file, aligns with at least one timecode included in an assertion check in the media assertion schedule; identifying an assertion condition included in the assertion check; and validating the assertion condition using the observed media frame signatures included in each of the at least one received observed signature file.

Systems and methods are described for delivering regional content for a lineup over a national network. A content provider may select a particular regional broadcast for inclusion in a regional service lineup. The content provider may be able to broadcast multiple, or even all, services nationally. At regional distribution centers, a multiplexer may select only those services that are desired for the region in response to in-stream signals. In some instances, a single region-specific version of a given service may be selected from multiple versions broadcasted nationally. The regional lineup, including the selected services, can then be multiplexed and transmitted to customers throughout the region.

A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.

An information processing device includes a control unit that determines whether or not a terminal device and an imaging device are associated with each other on the basis of first identification information received from the terminal device and second identification information received from the imaging device, and sets the terminal device as a destination of transmission of a return video image on the basis of a determination result.