An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation which may be efficiently processed to determine correspondence. Applications of the interface and system include a VCR, medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

An example to predict demographics for impressions includes a prediction manager to: determine that first demographic data corresponding to a first database proprietor subscriber does not match second demographic data corresponding to a media delivery device, both the first and second demographic data corresponding to an impression; obtain third demographic data corresponding to an Internet protocol address, the third demographic data obtained from a second database proprietor; and generate matched demographic data based on comparing the third demographic data to the first demographic data; and a modeler to generate a prediction model based on the matched demographic data, the prediction model to predict fourth demographic data for the impression.

The present disclosure describes a content consumption monitor (CCM) that determines surges in content consumption based on changes in content consumptions scores. The CCM determines the content consumptions scores for domains and/or organizations (orgs) based on session events generated by different devices/users from the org and/or domain, a number of events generated by the org/domain, content and/or user interactions with the content indicated by the events, relevancy scores of the content to one or more topics, and/or other criteria. The CCM detects surges in consumption or interest in a topic for the domain/org when the consumption score reaches a threshold and/or within a period of time. The CCM may adjust the consumption score based on the changes in the relevancy, number of events and/or the number of users over different time periods. Other embodiments may be described and/or claimed.

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.

This application provides a live streaming processing method performed by an electronic device. The method includes: displaying a live streaming room, the live stream room having a host account, a host sub-account and multiple viewer accounts, the host sub-account being used for assisting the host account of the live streaming room in operation; receiving real-time live streaming data of the live streaming room, and displaying a live streaming content on a live streaming room page according to the real-time live streaming data, the real-time live streaming data collected from the host account and the viewer accounts; and displaying, in response to a live streaming room operation of the host sub-account, an operation result of the live streaming room operation of the host sub-account in the live streaming room, wherein the operation result of the live streaming room operation updates the live streaming content on the live streaming room page.

A system includes a computing platform having processing hardware and a memory storing an asset library and software code including a recommendation engine. The processing hardware executes the software code to receive, from a user, group generation data and a preferences profile of the user, the group generation data identifying a group including the user and another user, and to send, to the other user, an invitation to join the group. The processing hardware also executes the software code to receive, from the other user, one of an acceptance or a refusal of the invitation, obtain, in response to receiving the acceptance, a preferences profile of the other user, generate, using the preferences profiles of the user and the other user, a group preferences profile for the group, and identify, using the recommendation engine and the group preferences profile, one or more assets in the asset library for the group.

Methods and systems are provided for bitrate adaptation of a video asset to be streamed to a client device for playback. The method includes selecting a representation from a manifest which expresses a set of representations available for each chunk of the video asset and generating a dynamic manifest for the video asset in which the representation selected for the at least one chunk is recommended for streaming to the client device. The selection of the representation recommended for the chunk may be based on at least one of historic viewing behavior of previous viewers of the chunk, content analysis information for the chunk, a level of available network bandwidth, a level of available network storage, and data rate utilization information of network resources including current, average, peak, and minimum data rate of network resources.

Systems and methods for enhancing user experience in accessing media of a certain content type by outputting the media on a nearby device that is better suited for access. For example, a media guidance application may determine that a user is accessing, on his/her smartphone, a digital page (e.g., a website, a newsfeed, etc.) that features embedded content (e.g., photos, movies, music, etc.). In response to determining that the user has navigated to an embedded content, such as a video clip, the media guidance application may determine a device in the vicinity of the user that is better suited than the user's smartphone for playback of the video clip. For example, a nearby smart television may have a larger screen, better sound output, and a better display resolution than the smartphone. As a result, the media guidance application may cause the smart television to output the video clip.

Methods, systems, and media for delivering manifestless streaming media content are provided. In some embodiments, the method comprises: receiving, from a user device, a request for a URL corresponding to a format of a live stream that is provided in a plurality of formats, wherein the live stream comprises a plurality of segments for each of the plurality of formats and wherein each segment of the plurality of segments comprises a respective sequence number; resolving the request to a specific segment of the live stream based on the URL, wherein the resolving comprises: identifying the format of the live stream associated with the request from the plurality of formats based on the URL; identifying a sequence number associated with the request based on the URL; and identifying a segment of the plurality of segments corresponding to the identified format and having a sequence number matching the identified sequence number; loading a segment file corresponding to the specific segment; and returning the segment file to the user device in a response to the request.