Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for generating a scene emotion value for a scene based on a sequence of frame emotion values for a sequence of frames within the scene of a content. The content can include multiple scenes, and a scene can include multiple frames, where a frame emotion value can be generated for each frame. A frame emotion value can be generated based on scene metadata related to the scene, content metadata related to the content, and a frame metadata related to the frame.

Abstract: A method and system for controlling media-content presentation based on user presence and/or user profile. An example method includes a computing system determining a quantity of users present at a media-presentation device, the quantity being at least one. Further, the example method includes, based on the determining, the computing system using the determined quantity of users present at the media-presentation device as a basis to control what media content a media player outputs for presentation by the media-presentation device. For instance, based on the determined quantity of users the computing system could tailor a graphical user interface (GUI) that the media player outputs for presentation by the media-presentation device, such as by tailoring a set of channel options that a channel-selection GUI provides, among other possibilities.

Abstract: Disclosed herein are various embodiments, for a content display and clustering system. An example embodiment operates by receiving a request to display the plurality of content items. At each of multiple levels different pairs of content items are identified and a similarity score is computed for each pair. A subset of pairs for which their similarity score exceeds a similarity threshold for the respective level are identified and clustered. This process is repeated for one or more iterations at the same level, and then the process is repeated for each of the multiple levels. A final clustered subset is identified, and output for display, responsive to the request to display the plurality of content items.

Abstract: In one aspect, an example method in connection with a shared content viewing session in which multiple users are receiving and viewing respective instances of the same media content in a synchronized manner is disclosed. The example method includes (i) detecting that each of the multiple users respectively exhibits a threshold extent of physical reaction around the same time; (ii) responsive to the detecting, for each of the multiple users, generating and/or storing respective visual content representing that user's physical reaction; (iii) generating a visual content composition that includes at least the generated and/or stored visual content for each of the multiple users; and (iv) outputting for presentation, the generated visual content composition.

Abstract: Disclosed herein are various embodiments, for a content display and clustering system. An example embodiment operates by receiving a request to display the plurality of content items. At each of multiple levels different pairs of content items are identified and a similarity score is computed for each pair. A subset of pairs for which their similarity score exceeds a similarity threshold for the respective level are identified and clustered. This process is repeated for one or more iterations at the same level, and then the process is repeated for each of the multiple levels. A final clustered subset is identified, and output for display, responsive to the request to display the plurality of content items.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for generating a scene emotion value for a scene based on a sequence of frame emotion values for a sequence of frames within the scene of a content. The content can include multiple scenes, and a scene can include multiple frames, where a frame emotion value can be generated for each frame. A frame emotion value can be generated based on scene metadata related to the scene, content metadata related to the content, and a frame metadata related to the frame.

Abstract: Disclosed are mechanisms for selecting a recommended item for a current item being viewed by a user account based on a view history of the user account with reduced bias. For a current item being viewed by the user account represented by a current node of a co-watch graph, embodiments can select a recommended item represented by an associated node in the co-watch graph likely being viewed by the user account, and determine a probability of the recommended item likely being viewed. The co-watch graph can be generated based on a view history of the user account. An edge between a first node and a second node of the co-watch graph can have a weight representing a number of co-occurrence times when the first item represented by the first node and the second item represented by the second node are viewed in sequence within a predetermined time interval.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for generating a scene emotion value for a scene based on a sequence of frame emotion values for a sequence of frames within the scene of a content. The content can include multiple scenes, and a scene can include multiple frames, where a frame emotion value can be generated for each frame. A frame emotion value can be generated based on scene metadata related to the scene, content metadata related to the content, and a frame metadata related to the frame.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for object identification and similarity analysis for content acquisition. An example embodiment operates by determining a first content item based on an amount of requests for the first content item. A first object may be identified based on an amount of instances that the first object is indicated by the first content item. Based on the first object, demographic information for the first content item may be determined. A second content item may then be requested based on an amount of attributes of the first object matching an amount of attributes of a second object indicated by the second content item, and the demographic information for the first content item matching demographic information for the second content item.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product aspects, and/or combinations and sub-combinations thereof, for generating trailers (previews) for multimedia content. An example aspect operates by generating an initial set of candidate points to generate a trailer for a media content; determining conversion data for each of the initial set of candidate points; determining an updated set of candidate points based on the conversion data; determining an estimated mean and upper bound for each of the updated set of candidate points; computing a value for each of the updated set of candidate points; generating a ranked list based on the value computed for each of the updated set of candidate points; and repeating the process until an optimal candidate point is converged upon.