Disclosed is an apparatus and method for VR sickness reduction based on VR sickness assessment. According to an embodiment of the inventive concept, an apparatus for reducing virtual reality (VR) content cybersickness includes a first module extracting feature information about each of predetermined cybersickness precipitating factors through analysis of VR content, and a second module determining a cybersickness precipitating factor requiring cybersickness reduction among the cybersickness precipitating factors based on the extracted feature information about each of the cybersickness precipitating factors, and generating the VR content as VR content having a cybersickness score not greater than a predetermined reference cybersickness score, by performing the cybersickness reduction on corresponding feature information, using a deep learning neural network pre-learned for each of the respective determined cybersickness precipitating factor.

A system for assisting a content consumer to select content services, the system including a processor that is configured to execute a matching algorithm. The matching algorithm comprises interviewing the content consumer for questions in a plurality of categories, determining a point system for answers obtained by the interviewing step, wherein the answers indicate entertainment interests of the content consumer; calculating a service score for each content service based on the point system, wherein the service score indicates an agreement between a content service and the entertainment interests of the content consumer; and selecting a pre-determined number of content services based on the service score.

A request associated with a user for content recommendation may be determined. At least one content item indicative of a viewing history associated with the user may be determined. The at least one content item indicative of the viewing history associated with the user may include content that the user has previously watched. Data associated with at least one image associated with each of a plurality of candidate content items may be determined. The plurality of candidate content items may include secondary content items that may be recommended to the user. Based on comparing data associated with at least one image associated with the at least one content item with the data associated with the at least one image associated with each candidate content item, at least one candidate content item may be determined. An indication of the at least one candidate content item may be sent, to a device associated with the user.

A system for customizing text messages in modifiable videos of a multimedia messaging application (MMA) is provided. In one example embodiment, the system includes a processor and a memory storing processor-executable codes, wherein the processor is configured to analyze recent messages of a user in the MMA to determine a context of the recent messages; determine, based on the context, a customized text message; select, based on the context, a list of relevant modifiable videos from a database configured to store modifiable videos, the modifiable videos being associated with preset text messages; replace the preset text messages in the relevant modifiable videos with the customized message; and render the list of relevant modifiable videos for viewing and selecting by the user, the rendering including displaying the customized text message in the relevant modifiable videos.

Aspects of the present disclose involve a method, a device, and a system comprising a processor and a machine-readable storage medium storing at a set of instructions for identification and authentication of user profiles associated with a digital television system and displaying information related thereto. In example embodiments, the method includes identifying a user profile registered with a content presentation device based on received identification data that includes biometric data. The method further includes receiving, from a server, identifiers of a set of recently watched channels associated with the user profile and causing presentation of a recent channels interface that includes selectable elements corresponding to the set of recently watched channels.

A method of supporting Adaptive Bit Rate, ABR, video resolution shaping of a video data stream of a video session transferred by a User Plane Function, UPF, in a Service Based Architecture, SBA, domain. The video resolution shaping is performed by the UPF implementing a Reinforcement Learning Agent, RLA, operating with an observation space having a determined video resolution of a received video data stream, a reward space having a reward referring to a required video resolution, and an action space having video resolution shaping levels to be applied at the received video data stream. Complementary methods and devices for performing such a method in an SBA domain deployed in a telecommunications system are disclosed.

Data processing systems and methods are disclosed for augmenting video content with one or more augmentations to produce augmented video. Elements within video content may be identified by spatiotemporal indices and may have associated values. An advertiser can pay to have an augmentation added to an element that, for example, advertises the advertiser's goods and/or includes a link that, when activated, takes a user to the advertiser's web site. Elements may have associated contexts that can be used to determine augmentations and element value, such as a position and/or current use of the element.

A method utilizes Artificial Intelligence (AI) system to broadcast a real-time event to a particular broadcast audience. The AI system receives a profile of a particular broadcast audience for a real-time event, and concurrent real-time Audio/Video (/V) streams for a particular portion of the real-time event. The AI system ranks the concurrent real-time A/V streams for the particular portion of the real-time event based on the types of event activities depicted in each of the concurrent real-time A/V streams and the profile of the particular broadcast audience for the real-time event; selects a particular real-time A/V stream, from the concurrent real-time A/V streams, for the particular broadcast audience based on the ranking; and directs a performance of a broadcast action related to the selected particular real-time A/V stream.

Systems and associated methods are described for providing content recommendations. The system selects, using a multi-armed bandit solution model, a first plurality of content categories based on a reward score of each content category. The categories are displayed. When a user selects an item from the displayed categories, the system finds all categories that include the selected item, but rewards only the category with the highest score. The system selects, using the multi-armed bandit solution model, the second plurality of content categories based on the updated reward score of each content category. The categories are then displayed. The system may also repeat the steps to refine the multi-armed bandit solution model.

A method and system for editing a video on the basis of a context obtained using artificial intelligence. According to an embodiment of the present invention, the method for editing a video may comprise the steps of: establishing a plurality of contexts for an input video by analyzing the video through an artificial intelligence model, and taking, from the video, a plurality of clips corresponding to the established plurality of contexts; generating a user interface through which to receive a certain context selected from the plurality of contexts; providing, through the generated user interface, a plurality of clips that has been taken from the video for the context selected from the plurality of contexts through the generated user interface; and generating a highlight image for the selected context for the video by merging clips together that have been selected from the plurality of clips provided through the user interface.