The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

A method and digital signage player for managing display of a distributed digital signage content. The digital signage player stores the distributed digital signage content, and a local placement target for the distributed digital signage content. The digital signage player displays the distributed digital signage content in accordance with the local placement target. The digital signage player exchanges messages with a neighbor digital signage player, for increasing the local placement target of the distributed digital signage content at the request of the neighbor digital signage player. The neighbor digital signage player also displays the distributed digital signage content in accordance with its own placement target, which needs to be decreased. The digital signage player ultimately increases the local placement target of the distributed digital signage content based on the messages exchanged with the neighbor digital signage player.

According to an embodiment, an image display device includes: a display; a memory storing one or more instructions; and a processor executing the one or more instructions stored in the memory, wherein the processor executes the one or more instructions: to determine whether it is a recommended time for outputting advertisement content, from a user's log data, based on a first trained model using one or more neural networks; to determine a recommended attribute of an advertisement display region from the user's log data, based on a second trained model using the one or more neural networks, when it is determined that it is the recommended time for outputting the advertisement content; and to adjust an attribute of the advertisement display region based on the determined recommended attribute and control the display to output the advertisement content in the attribute-adjusted advertisement display region.

The current invention relates to a computer-generated method for optimizing placement of advertising content to consumers' TV's using a programmatic TV bidding model. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which an advertiser can access relevant information about inventory and success of a given placement.

According to a shared signboard service of the present invention, traditional wall signboards, which are individually installed and independently managed by respective store owners mainly to display a store name, are recreated into network-connected digital shared signboards by fusion with ICT technology, so that a self-advertisement, a third-party advertisement, and public information content can be displayed in addition to displaying a trademark, and multipurpose use is possible. In addition, as a signboard replacement procedure can be implemented only by changing display content, sign replacement costs can be reduced, and environmental problems can be prevented.

A health care provider (HCP) engagement engine is disclosed. The HCP engagement engine facilitates effective communication between pharmaceutical sales representatives (medical reps) and HCPs by generating, using machine learning algorithms, messages for the medical reps to send to HCPs. The recommended messages may be sent over a network and may include email messages, text messages, or online chat messages. The recommended messages may be drafted entirely by the engagement engine or may be drafted as addenda to messages already used by the medical reps. The HCP engagement engine uses historical data on actions performed by the HCPs and medical reps, as well as data collected from historical message recommendation events, in order to produce message recommendations.

Systems and methods for selecting content based on an event associated with a device identifier are provided. One or more processors can receive a request to serve content. The processors can identify a device identifier associated with the request. The processors can determine, from the device identifier, an event for which to serve content. The processors can determine, from the request, a length of time between a time the request to serve content is received and a time at which the event is scheduled to occur. The processors can select, based on the determined length of time and event parameters associated with the event, content for display and provide the selected content for display at a computing device associated with the device identifier.

Among other things, videos and commercials are downloaded to a mobile device for storage on the mobile device and later playout on the mobile device. The downloading includes downloading of metadata associated with the commercials and based on which the mobile device can select commercials for insertion into videos being played back to the user of the mobile device. The commercials to be downloaded are selected based on one or a combination of any two or more of the location of the user, the type of mobile device, and personally-identifiable information about a user of the mobile device.

A service provider may receive item price information and/or point of sale (POS) transaction information from a plurality of merchant devices associated with a plurality of merchants. The service provider may categorize the plurality of merchants according to the types of items offered by the respective merchants, and may further categorize the merchants according to the locations at which they conduct business. The service provider may subsequently determine a price recommendation or other pricing information for a particular item offered by a particular merchant. A merchant device of the particular merchant may present the pricing information in a user interface that enables the merchant to view projected sales at various different price points. Further, the merchant may be able to specify one or more factors used for determining the recommend price, such as a desired business model, a desired clientele, a desired profit margin, or the like.

This disclosure describes systems, methods, and devices related to network resource management and content delivery. A method may include a first device determining a first bandwidth demand associated with a second device sending a first addressable advertisement using a data over cable service interface specification (DOCSIS) bandwidth using a first advertisement spot for a first linear segment addressability (LSA) television channel, and determining a second bandwidth demand associated with the second device sending a second addressable advertisement using the DOCSIS bandwidth for presentation using a second advertisement spot. The method may include determining that the first bandwidth demand is below a threshold bandwidth, and determining that the second bandwidth demand exceeds the threshold bandwidth. The method may include sending a reference to the first addressable advertisement over the DOCSIS bandwidth for presentation using the first advertisement spot and, and determining a recommendation associated with presentation of the second addressable advertisement.