Systems and methods are disclosed herein for detecting a first reaction by a user when consuming a media asset at a first time, where a first magnitude of the first reaction exceeds a first threshold. The systems and methods may determine whether a second reaction by the user occurred when the user consumed the media asset at a second time that is prior to the first time, where a second magnitude of the second reaction exceeds a second threshold, and may recommend the second media asset to the user.

Systems and methods are described herein for recommending content based on a mood score associated with a user profile. The system accesses the viewing history of the user profile to determine media assets consumed and the mood score associated with each of the consumed media assets of the plurality of media assets. A cumulative mood score is calculated based at least in part to determine if the total score is below a mood threshold. Based on the cumulative mood score being lower than the mood threshold, the system generates for presentation, on the consumer device, one or more media assets with a positive mood score.

A server includes: a video data acquiring unit configured to acquire video data in which a game is imaged; a storage configured to store the video data; an image determining unit configured to determine whether or not target image data, which is data of a target image indicating an advertisement client, is included in the stored video data; an advertisement setting unit configured to generate, when the target image data is included in the video data, advertisement setting data at a time when video based on the video data is displayed in an external display, the advertisement setting data being to be used for displaying, in the external display, an advertisement of the advertisement client corresponding to the target image; and a communication unit configured to be capable of sending the video data and the advertisement setting data to outside.

The serving of advertisements with (e.g., on) video documents may be improved in a number of ways. For example, a system may (a) accept information defining at least one ad spot associated with at least one instance of an video document, (b) accept offers to have advertisements served in the ad spot(s), and (c) arbitrate among competing advertisements, using at least the offers, to determine at least one advertisement to be served in that ad spot(s). As another example, a system may (a) accept relevance information for an advertisement, (b) determine at least one video document using the accepted relevance information, (c) present information about the video document(s) to an advertiser associated with the advertisement, and (d) accept, from the advertiser, an offer to have its advertisement served with at least one of the video document(s) accepted. As yet another example, a system may (a) accept relevance information for an video document, (b) determine a plurality of advertisements relevant to the video document using the relevance information and serving constraints of the advertisements, and (c) select at least one of the determined relevant advertisements to be served with the video document. Examples of video documents include video files published on the Internet, television programs, live or recorded talk shows, video-voice mail, segments of an video conversation, etc.

A system for automatically managing the delivery of media assets allocates the media assets to delivery slots of a media delivery servers so that consumers will receive the media assets when they consume digital media programming at times that correspond to the delivery slots. An example is the automated allocation of sponsored videos to television programs airing on a particular afternoon. The system includes data stores and a campaign manager system. The campaign manager system will automatically allocate digital media assets to delivery slots in a campaign to generate scheduling files that media servers will use to present the allocated media assets to consumers during the assigned delivery slots via media consumption devices.

In some embodiments, a method receives a first set of probabilities mapping a behavior to a user for a set of behaviors in a video delivery system. A first part of a model is used to predict the first set of probabilities. The method receives a second set of probabilities mapping a user to a behavior for a set of users that are using an account on the video delivery system. A second part of the model is used to predict the second set of probabilities. A combined probability is calculated for the set of behaviors and the set of users based on the first set of probabilities and the second set of probabilities. The method updates a second parameter of the second part of the model while keeping a first parameter of the first part of the model fixed and outputs the second parameter of the second part of the model upon determining the training of the model is finished.

Aspects of the subject disclosure may include, for example, a device, that has a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, where the operations include detecting each individual of an audience viewing media content on user equipment; retrieving a user profile for each individual of the audience resulting in user profiles; creating a group profile from the user profiles; determining, based on the group profile, a recommendation for viewing a candidate media content; and providing the recommendation to the user equipment for the audience. Other embodiments are disclosed.

Systems and methods are provided herein for determining reduction of interest in a content series and to increasing the interest upon such determination. This may be accomplished by a device monitoring consumption of a content series to determine a pattern of consumption. The device may identify a change in the pattern of consumption indicative of a reduction of interest and determine a reason for the reduction in interest. Based on the reason for the reduction of interest, the device may provide an operation, such as a spoiler, to increase interest in the content series.

Methods, apparatus, systems and articles of manufacture to impute media consumption behavior are disclosed. An example system includes one or more media meters to obtain tuning data, one or more people meters to obtain viewing data, and one or more servers to, in response to a determination that a difference satisfies a first threshold, determine that a first subset of the tuning data associated with first panelist households having tuned to first media in a first area exhibits local bias, determine that a second subset of the viewing data associated with second panelist households having viewed the first media in the second area represents heavy viewing, and impute the second subset of the viewing data for the first subset of the tuning data in response to the second subset of the viewing data representing heavy viewing.

A content distribution system according to one embodiment acquires content data of existing content representing a virtual space, analyzes the content data to dynamically set at least one scene in the content as at least one candidate position for cueing in the content, and sets one of the at least one candidate position as a cueing position.