Embodiments relate to configuring artificial-intelligence (AI) decision nodes throughout a communication decision tree. The decision nodes can support successive iteration of AI models to dynamically define iteration data that corresponds to a trajectory through the tree.

Embodiments of the invention overcome the shortcomings of prior art by transforming the understanding of how different creative placements and location helps drive sales and other KPIs to a computerized methodology that may allow advertising planners and buyers to generate plans that meet these expectations on effectiveness of their advertising campaign. Aspects of the invention fusing the “probability of exposure” estimates with segment level data to provide layers of intelligence in determining the probability estimates for sales conversion or other KPIs. Moreover, aspects of the invention may predict based on various models the reach and frequency relationship tradeoff for different impression levels.

A method for determining one or more publishers for an advertising campaign including receiving an input request comprising a set of metadata from an advertiser device; extracting the set of metadata; generating a plurality of success scores based on the extracted set of metadata using at least one artificial intelligence (AI) or machine learning (ML) algorithm, one or more parameters of the at least one AI or ML algorithm determined via training and testing performed using one or more data sets comprising one or more previous results, and each success score corresponds to one of a plurality of publishers; selecting the one or more publishers from the plurality of publishers based on the one or more success scores; implementing the advertising campaign using the selected publishers; collecting the results of the advertising campaign; and adding the collected results to the one or more previous results.

One or more computing devices, systems, and/or methods for implementing a model for serving exploration traffic are provided. An amount of spend by a content provider to provide content items of the content provider through a content serving platform to client devices of users is determined. A number of exploration impressions of users viewing exploration content items of the content provider over a timespan is determined. A return on exploration impression metric is determined for the content provider based upon a ratio of the amount of spend to the number of exploration impressions. The return on exploration metric is used to rank available exploration content items of content providers for serving exploration traffic.

A system to dynamically generate, monitor and optimize an allocation of resources includes a processor-based server to process requests received from the client devices. The processor-based server includes a server processor to generate the allocation of resource sharing one or more display devices selected based on an allocation criterion defined by the information emitter, target rating point goal, a geolocation, a format, and a quality coefficient of each display device in the set of available display devices. The server processor monitors availability of previously unavailable display devices and track real-time changes to the quality coefficients for each display device in the updated set. The server processor dynamically updates and optimizes the allocation of resources based on the updated quality coefficients for the updated set of available display devices.

A system for providing advertisements with search results in response to a search query comprises a front end and an advertisement server. The front end is configured: to receive a search query; to send a first search request to a search server and sending a first advertisement request to an advertisement server, wherein the first search request includes the search query or information based on the search query, and wherein the first advertisement request includes the search query or information based on the search query and an indication that an advertisement response is not to be provided; to receive search results from the search server; and to send at least some of the search results to the advertisement server in a second advertisement request, wherein the second advertisement request includes an indication that an advertisement response is to be provided. The advertisement server is configured: in response to receiving the first advertisement request, to search for advertisements related to the search query to produce plural advertisement results each with an associated score; in response to receiving the second advertisement request, to modify the score of at least one of the plural advertisement results; to rank the plural advertisement results according to their scores; to select one or more of the highest ranked plural advertisement results; and to send an advertisement response to the front end, the advertisement response including the selected one or more highest ranked plural advertisement results. The front end is configured to provide the search results with the selected one or more highest ranked plural advertisement results.

In the world of digital advertising, optimally allocating an advertisement campaign within a fixed pre-defined budget for an advertising duration aimed at maximizing number of conversions is very important for an advertiser. Embodiments of present disclosure provides a robust and easily generalizable method of optimal allocation of advertisement campaign by formulating it as a constrained Markov Decision Process (MDP) defined by agent state comprising user state and advertiser state, action space comprising a plurality of ad campaigns, state transition routine and a cumulative reward model which rewards maximum total conversions in an advertising duration. The cumulative reward model is trained in conjunction with a deep Q-network for solving the MDP to optimally allocate advertisement campaign for an advertising duration within a constrained budget.

A system and method are provided for a pedestrian thoroughfare portable media projection kiosk. The method provides a portable kiosk chassis located in a pedestrian thoroughfare. A media projection subsystem attached to the kiosk projects a media message and creates a media enablement signal. The media message may be a visual display, an audio broadcast, or both. The method verifies that media has been projected in response to receiving a media enablement signal. Verification information is supplied that includes the media enablement signal, and the verification information is communicated to a server. The verification information may be communicated using a cellular telephone, an IEEE 802.11 Wireless Local Area Network (WLAN) device, an IEEE 802.15 Wireless Personal Area Network (WPAN) device, or combinations thereof. Alternatively, or in addition, the kiosk may provide a publically accessible cellular telephone booster, a WLAN access point (AP), WPAN AP, or combinations thereof.

A networked computerized advertising system used for integrating, processing and displaying location-based advertising information is provided. The system comprises at least one computing device, and a network that connects the computing device with multiple playback endpoints. The computing device includes a data storage subsystem component that stores information about the multiple end points, a data entry subsystem component that allows input of the information about the multiple end points, and a data analytics component programmed to process the information about the multiple end points and compute optimal advertising playback plans for each endpoint. Playbacks at endpoints are continuously monitored, and the playback plans are repeatedly reconstructed to provide flexible advertising campaigns to be customized in accordance with the schedule and the operations of the host business.

Allocating bids for providing content within a segmented campaign is controlled to ensure that an event rate associated with the provided content meets or exceeds a threshold rate. A campaign-level event rate, associated with the provided content, is estimated and provided as a feedback signal. This feedback signal is employed to dynamically update bid allocations for each of the segments, which in turn varies the number or rate of provided impressions and events. Such feedback enables the control of the campaign-level rate and ensures that the campaign-level rate meets or exceeds the rate threshold. To control these rates, the number of total impressions, as well as the number of associated events, is temporally sampled across the campaign segments. Based on the number of impressions and events, the campaign-level event rate is estimated and employed as the feedback signal. Updating the bid allocations may be based on the Beta Distribution.