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.

Methods, apparatus, systems and articles of manufacture to perform media device asset qualification are disclosed. An example apparatus includes at least one memory, and at least one processor to execute instructions to at least identify a first set of candidate media device assets for disqualification, the candidate media device assets including A) a signature and B) a media identifier that identifies media, generate a hash table using a second set of the candidate media device assets, determine one or more counts of matches between C) a first signature and a first media identifier of a first candidate media device asset of the second set and D) respective signatures and media identifiers of multiple ones of the second set using the hash table, the multiple ones of the second set not including the first candidate media device asset, and load the first signature into a reference database as a reference signature.

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.

Certain exemplary embodiments disclosed herein relate to systems and/or methods for distributing advertisements from a central advertisement network to one or more peripheral devices at a location via a local advertisement server. In certain exemplary embodiments, the local advertisement server within a location receives advertisements from the central advertisement network and rebroadcasts them to peripheral devices within that location. Advertising information may be tracked and reported, e.g., for accounting, revenue-sharing, and/or other purposes in certain exemplary embodiments. Thus, in certain exemplary embodiments, the distribution of advertisements is provided to peripherals via a non-web- and non-PC-dependent network. Moreover, in certain exemplary embodiments, reporting and advertising related communications are substantially bi-directional regardless of device type. Certain exemplary embodiments provide revenue sharing among some or all of the central advertising network provider, the proprietors of locations, operators tasked with maintaining the local ad server and/or the peripheral devices, etc.

A set of criteria for deploying an advertisement campaign to a set of audience members associated with a region are received. An audience propensity dataset associated with media platforms are received. The media platforms can include a first and second set of media platforms. Content output by the first set of media platforms can be monitorable by an organization, and content output by the second set of media platforms is not monitorable by the organization. A pricing dataset indicating pricing information associated with the first set of media platforms at the region is received. A viewing dataset indicating viewing information for the set of audience members using the first set of media platforms is received. A media plan generated based on a predicted viewership dataset, a tier dataset, and a cost dataset.

A method is provided, including the following operations: monitoring gameplay activity in a plurality of game sessions, wherein the monitoring includes, for each game session, analyzing the gameplay activity in said game session to predict future gameplay activity in said game session; identifying one or more characteristics of a plurality of spectators interacting with a virtual character, wherein each of the spectators interacting with the virtual character accesses, over a network, a channel that is attributed to the virtual character; through the channel, providing access to the spectators to spectate a selected game session that is one of the plurality of game sessions, selected based on the predicted future gameplay activity and based on the characteristics of the plurality of spectators.

A system and method for rapidly and scalably tracking attentiveness. The system includes means for collecting relevant data streams from a plurality of client devices while consumers view content, means for analysing the collected data with an AI-driven module that outputs one or more attentiveness metrics indicative of real attention, and means for synchronising the collected data with the attentiveness metrics. The system provides the ability to synchronise attentiveness metrics with other data streams to make accessible the reasons that drive attention. A digital advertising campaign can be optimised using an effectiveness data set that expresses evolution over time of an attentiveness parameter. An effect on the attentiveness parameter caused by an adjustment to a target audience can be predicted and evaluated against a campaign objective, which can be updated for predictions that yield a positive effect.

A system and method for automatically preparing personalized video presentations using a dynamic scene replacement engine which uses data points relating to a specific viewer to optimize the content of a video presentation for that specific viewer in order to increase the overall emotional effectiveness of the video presentation. The system and method for automatically preparing personalized video presentations operates to identify stock personalizing video content clips which can replace generic scenes in a raw video presentation to add personalizing material designed to appeal to the particular viewer to the presentation. Through this action, a unique personalized video presentation may be automatically prepared on demand for every particular viewer.

Apparatus, systems, articles of manufacture, and methods are disclosed for handling exceptions reported by media device meters. An example apparatus includes a static display detector to determine whether current measurements for a media presentation device at a time corresponding to an exception reported by a media device meter indicate the media presentation device was in a static display state at the time corresponding to the exception. The example apparatus includes a muted viewing detector to determine whether the media presentation device was in a muted viewing state at the time of the exception based on an audio level associated with the media presentation device, and an exception modifier to determine whether to modify the exception based on whether the media presentation device was in the static display state and whether the media presentation device was in a muted viewing state at the time of the exception.

Facilitating separation of intended and non-intended browsing traffic in browsing history advanced networks (e.g., 4G, 5G, and beyond) is provided herein. Operations of a system can comprise determining respective contradiction values for second-level domains of a group of second-level domains in observed browsing history traffic. The operations can also comprise separating intended network traffic from non-intended network traffic based on the respective contradiction values. The respective contradiction values can indicate levels of inconsistency between the observed browsing history traffic and a determined popularity ranking.