An electronic apparatus includes a processor. The processor is configured to: obtain information about weighted values respectively assigned to a plurality of items having values that represent content features of a plurality of pieces of content, wherein the weighted values are assigned as higher weight values to items corresponding to the content features preferred by according to genres of content; identify a user content viewed by a user of the electronic apparatus; calculate similarities in values of the plurality of items, respectively, between a plurality of pieces of recommendable content and the user content, respectively; calculate recommendation scores of the plurality of pieces of content, based on the calculated similarities and the weighted values assigned to the items according to the genres; and perform a recommendation operation for one or more content pieces, of which the calculated recommendation score is equal to or higher than a preset ranking.

Systems and methods for providing a first user with recommendations of media assets for inclusion in a playlist for a second user based on the second user's viewing activity. These systems and methods receive, from the second user, an expression of disinterest in a media asset included in the playlist for the second user, update a user profile associated with the second user based on the expression of disinterest, and determine a recommendation for another media asset based on the updated user profile associated with the second user. The systems and methods provide the recommendation to the first user. By recommending media assets that the second user is least likely to object to, these systems and methods reduce the frequency of disruptive requests for media assets from the second user.

Systems and methods are provided herein for displaying recommendations that are temporally relevant to activities of a user and are contextually relevant to a portion of viewed media. This may be accomplished by a media guidance application identifying activities a user has planned, as well as respective times for which each of the plurality of activities was planned to be performed by the user. The media guidance application may filter the activities by determining which of the first plurality of activities has a corresponding respective time that is within a threshold period of time. The media guidance application may then identify characteristics of each filtered activity and of a media asset that the user is consuming at the present moment, and may compute whether the characteristics match. If the characteristics match, the media guidance application may generate for display a recommendation relating to the respective activity.

A content recommendation method that includes: acquiring content cover images corresponding to multiple pieces of content accessed by a user account; acquiring cover image features of the multiple content cover images, and determining user account features of the user account according to the cover image features of the multiple content cover images; on the basis of cover image features of content to be recommended and the user account features, determining an access probability value of the user account accessing the content to be recommended; and providing, according to the access probability value, the content to be recommended to the user account.

Systems, methods, and computer-readable media for determining at least one valid mood for a collection of media content items of a media library are provided.

Disclosed is a display apparatus comprising: a display; a user input unit; and a processor configured to identify a user's viewing time based on a user's viewing history, create a list of content to be provided within the identified viewing time based on the viewing history and display the created content list on the display, and select at least one piece of content in the content list for viewing schedule based on a user input through the user input unit.

Methods, apparatus and systems related to production of a movie, a TV show or a multimedia content are described. In one example aspect, a system for producing a multimedia digital content includes a pre-production subsystem configured to receive information about a storyline, cameras, cast, and other assets for the content from a user. The pre-production subsystem is configured to generate one or more machine-readable scripts that include information about one or more advertisements. The system includes a production subsystem configured to receive the one or more machine-readable scripts from the pre-production system to obtain a footage according to the storyline. The production subsystem is further configured to embed one or markers corresponding to the one or more advertisements in the footage. The system also includes a post-production editing subsystem configured to detect the one or more markers embedded in the footage and replace each of the one or more markers with a corresponding advertising target.

A media guidance application may monitor a conversation among users, and identify keywords in the conversation, without the use of wakewords. The keywords are used to search for media content that is relevant to the on-going conversation. Accordingly, the media guidance application presents relevant content to the users, during the conversation, to more actively engage the users. A conversation monitoring window may be used to present conversation information as well as relevant content. A listening mode may be used to manage when the media guidance application processes speech from a conversation. The media guidance application may access user profiles for keywords, select content types, select content sources, and determine relevancy of media content, to provide content in context of a conversation.

A method for playing videos can include: playing a first video; displaying a video viewing portal on a playback interface of the first video, wherein the video viewing portal is configured for viewing of videos related to the first video; switching, in response to no trigger operation on the video viewing portal being detected within a first reference duration, the video viewing portal to a float window corresponding to a second video related to the first video; and playing the second video in response to a trigger operation on the float window.

Disclosed is a system for generating personalized recommendations based on dynamic and customized content selections and modeling of the content selections. The system may receive a request with an identifier and a query, and may obtain a particular recommendation configuration based the identifier and the query. The system may retrieve a set of content that satisfies the query and that is identified with at least one content prioritization parameter specified in the particular recommendation configuration, may generate a set of models of one or more model types that model relevance between the set of content and a different event specified in the particular recommendation configuration, and may compute a score for each content in each model based on the modeled relevance. The system may present recommended content in a different order than the set of content based on aggregate scores compiled for each content from the set of models.