Television is the largest advertising category in the United States with over 65 billion spent by advertisers per year. A variety of different targeting algorithms are compared, ranging from the traditional age-gender targeting methods employed based on Nielsen ratings, to new approaches that attempt to target high probability buyers using Set Top Box data. The performance of these different algorithms on a real television campaign is shown, and the advantages and limitations of each method are discussed. In contrast to other theoretical work, all methods presented herein are compatible with targeting the existing 115 million Television households in the United States and are implementable on current television delivery systems.

Non-transitory computer-readable media, systems, apparatus, and computer-implemented methods are described herein for facilitation of generation and selective provision of a modular advertising unit over a plurality of communication channels to a plurality of end user computing devices. In various embodiments, the modular advertising unit comprising may include a first graphic configured to be operable by a user with an end user computing device to reveal, in place of at least a portion of the first graphic, a second graphic to the user. In various embodiments, the modular advertising unit may also include instructions configured to cause the end user computing device, in response to execution of the instructions by the end user computing device, to automatically provide a report, to the computing device or another computing device associated with an advertising entity, about operation of the first graphic.

Methods and apparatus to monitor media presentations are disclosed. Disclosed example apparatus include means for collecting demographic information from a user with a registrar of a media device, means for transmitting the demographic information to a central facility from the registrar, and means for storing a panelist identifier identifying the user in a shared memory of the media device, the panelist identifier accessible to a first monitoring-enabled application and a second monitoring-enabled application separate from the registrar, the panelist identifier to be retrieved by the first monitoring-enabled application, the first monitoring-enabled application to present media, the first monitoring-enabled application to collect monitoring information if the panelist identifier is in the shared memory and to disable collection of media monitoring information if the panelist identifier is not in the shared memory.

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for increasing the performance of an advertisement network by monitoring requests for advertisements from applications, detecting patterns, and developing and implementing remedial actions to increase system performance.

The disclosure includes a camera array comprising camera modules, the camera modules comprising a master camera that includes a processor, a memory, a sensor, a lens, a status indicator, and a switch, the switch configured to instruct each of the camera modules to initiate a start operation to start recording video data using the lens and the sensor in the other camera modules and the switch configured to instruct each of the camera modules to initiate a stop operation to stop recording, the status indicator configured to indicate a status of at least one of the camera modules.

Methods, apparatus, systems and articles of manufacture to de-duplicate partially-tagged entities are disclosed. An example method includes identifying a tagged audience for a first sub-entity, identifying a panel audience for the second sub-entity, determining a panel duplication between the first sub-entity and a second sub-entity, determining a duplicated audience based on the tagged audience, the panel audience, and the panel duplication, and determining a de-duplicated audience for the partially-tagged entity based on the duplicated audience and a total audience, the total audience including the tagged audience for the first sub-entity and the panel audience for the second sub-entity.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing data and analysis for advertising on networked devices. One of the methods includes creating a vector of identifiers representing an ad opportunity. The method includes linking data attributes that describe the ad opportunity to the identifiers. The method includes expressing the data attributes following predefined scheme of hierarchy. The method includes linking a taxonomy describing data attributes. The method includes obtaining outcome measurements of ad events associated with the ad opportunity. The method also includes associating user interaction events with the ad with at least one of the identifiers or data attributes associated with the identifier.

In general, systems, methods and computer readable media for data record compression using graph-based techniques are provided herein.

In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.

In one embodiment, a method includes providing an interface that permits a first user to broadcast a live video to one or more second users. The method also includes determining that at least one predetermined condition for taking a commercial break during the live video has been met. The method also includes, after determining that at least one of the predetermined conditions has been met, displaying a selectable option within the interface that permits the first user to begin the commercial break. The method also includes, after receiving an indication that the first user has selected the selectable option to begin the commercial break, beginning the commercial break by ceasing to display the live video to the one or more second users after a predetermined amount of time and displaying one or more commercials to the one or more second users during the commercial break.