Methods, systems, and machine-readable media are provided to facilitate content receiver control for particularized output of content items based on intra-content metrics. Observation data, corresponding to indications of detected content receiver operations associated with a content receiver and mapped to a first set of content items, may be processed. A first set of intra-content metrics may be detected. An audiovisual pattern of intra-content metrics may be mapped based on correlating the set of observation data with the first set of intra-content metrics. A second set of content items may be processed to detect a second set of intra-content metrics. A subset of the second set of content items may be selected based on a visual category and/or an audio category of the audiovisual pattern of intra-content metrics. The subset may be specified to cause a content receiver to modify operations to record and/or output content corresponding to the subset.

A method for generating an image depiction of particular content that includes a machine learning system programmed to receive profile data representing preferences for content. The machine learning system identifies preferences for content features based upon the profile data, accesses content data representing the particular content and other content, and classifies features of the content data and image data within an image database system according to content categories. The machine learning system generates an image depiction of the particular content by combining image data from the image database system, wherein the combining is based upon correlating the identified preferences of the profile with the classified content categories. The machine learning system receives feedback data responsive to the image depiction and reprograms a configuration of the machine learning system for generating an image depiction based upon the feedback data.

In various embodiments, an interactive streaming application plays back a media title via a client device. In operation, the interactive streaming application causes the client device to playback a first chunk of the media title. While the client device plays back the first chunk, the interactive streaming application determines a movement of an internet of things (“IoT”) device that is controlled by the user. The interactive streaming application performs reinforcement-learning operation(s) based on the first chunk and the movement to determine a second chunk of the media title to playback. The interactive streaming application then causes the client device to playback the second chunk of the media title. Advantageously, the interactive streaming application can automatically personalize the playback of the media title for the user based, at least in part, on movements of the IoT device.

A packet forwarding method. The method reacts to service function events promptly by recalculating a more streamlined service function path (SFP) for a packet flow of a service function chain (SFC). Service functions (SFs) and service function forwarders (SFFs) collaborate to serve a SFC packet flow and bypass SFs belonging to the same SF group which does not provides functional service to packets of the flow.

A packet forwarding method. The method reacts to service function events promptly by recalculating a more streamlined service function path (SFP) for a packet flow of a service function chain (SFC). Service functions (SFs) and service function forwarders (SFFs) collaborate to serve a SFC packet flow and bypass SFs belonging to the same SF group which does not provides functional service to packets of the flow.

Methods and apparatus to estimate demographics of a household are disclosed. An example method to determine demographics for non-panelist households includes calculating a first demographic constraint average and a second demographic constraint average based on a first demographic distribution of a first tuning event of a household and a second demographic distribution of a second tuning event of the household. The household is a non-panelist household. The example method also includes, based on the first demographic constraint average, determining a first likelihood of the household being associated with a first demographic constraint. The example method also includes, based on the second demographic constraint average, determining a second likelihood of the household being associated with a second demographic constraint. The example method also includes estimating a household characteristic of the household based on the first likelihood and the second likelihood.

This disclosure relates to methods, non-transitory computer readable media, and systems that determine multiple personas corresponding to a user account for digital content and train a persona classifier to predict a given persona (from among the multiple personas) for content requests associated with the user account. By using the persona classifier, the disclosed methods, non-transitory computer readable media, and systems accurately detect a given persona for a content request upon initiation of the request. Based on determining the given persona, in some implementations, the methods, non-transitory computer readable media, and systems generate a digital-content recommendation for presentation on a client device associated with the user account.

Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example apparatus includes a reach determiner to determine a population reach estimate of a union of time intervals for which media ratings data is available, the population reach estimate based on a pseudo universe estimate of a population audience corresponding to the union of the time intervals; a pseudo universe determiner to determine a pseudo universe estimate of a recorded audience corresponding to the union of the time intervals; determine the pseudo universe estimate of the population audience based on the pseudo universe estimate of the recorded audience; and iteratively update the pseudo universe estimate of the population audience to reduce an error; and a consistency checker to adjust the population reach estimate, the reach determiner to output the population reach estimate of the union.

Provided is a method and an apparatus for displaying a live broadcast room, a device, and a storage medium. The method includes: acquiring a live broadcast screenshot of at least one live broadcast room under a target classification label; inputting the live broadcast screenshot of the at least one live broadcast room into an image detection model to obtain a live broadcast screenshot that satisfies a set type condition; adding a display identifier to a live broadcast room corresponding to the live broadcast screenshot of the set type condition; and arranging and displaying the at least one live broadcast room according to the display identifier in a display interface corresponding to the target classification label.

A packet forwarding method. The method reacts to service function events promptly by recalculating a more streamlined service function path (SFP) for a packet flow of a service function chain (SFC). Service functions (SFs) and service function forwarders (SFFs) collaborate to serve a SFC packet flow and bypass SFs belonging to the same SF group which does not provides functional service to packets of the flow.