Transaction-enabled systems and methods for royalty apportionment and stacking are disclosed. An example system may include a plurality of royalty generating elements (a royalty stack) each related to a corresponding one or more of a plurality of intellectual property (IP) assets (an aggregate stack of IP). The system may further include a royalty apportionment wrapper to interpret IP licensing terms and apportion royalties to a plurality of owning entities corresponding to the aggregate stack of IP in response to the IP licensing terms and a smart contract wrapper. The smart contract wrapper is configured to access a distributed ledger, interpret an IP description value and IP addition request, to add an IP asset to the aggregate stack of IP, and to adjust the royalty stack.

The present disclosure describes transaction-enabling systems and methods. A system can include a facility including a core task including a customer relevant output and a controller. The controller may include a facility description circuit to interpret a plurality of historical facility parameter values and corresponding facility outcome values and a facility prediction circuit to operate an adaptive learning system, wherein the adaptive learning system is configured to train a facility production predictor in response to the historical facility parameter values and the corresponding outcome values. The facility description circuit also interprets a plurality of present state facility parameter values, wherein the trained facility production predictor determines a customer contact indicator in response to the plurality of present state facility parameter values and a customer notification circuit provides a notification to a customer in response.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform extracting meta features for an item to generate sparse feature embeddings for the item; reducing, using a multilayer perceptron, a dimension of the sparse feature embeddings to generate a representation vector for the meta features; extracting, using a recurrent neural network, sequential data from dense traffic features for the item over a period of time; and inputting the representation vector for the meta features and the sequential data from the dense traffic features into a multilayer neural network with a rectified linear unit (ReLU) activation function and a scoring layer to generate one or more performance metrics for the item. Other embodiments are disclosed.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.

Systems, methods and articles for optimizing the clearance of content, such as advertisements. The systems disclosed herein provide a greater chance that offers to buy advertisement placement opportunities from media providers are accepted by the media providers. This is achieved by matching advertisements to advertisement placement opportunities which match buyer goals and provider goals, and by using historical data related to advertisements that the seller has cleared. The system may optimize clearance for multiple buyers which are competing for the same advertisement placement opportunities at the same time.

A computer system and computer-implemented method for retail merchandise planning, including promotional product selection, price optimization and planning. According to an embodiment, the computer system for generating an electronic retail plan for a retailer comprises, a data staging module configured to input retail sensory data from one or more computer systems associated with the retailer; a data processing module configured to pre-process the inputted retail sensory data; a data warehouse module configured to store the inputted retail sensory data and the pre-processed retail sensory data; a state model module configured to generate a retailer state model for modeling operation of the retailer based on the retail sensory data; a calibration module configured to calibrate the state model module according to one or more control parameters; and an output module for generating an electronic retail plan for the retailer based on the retailer state model.

Branded content, or a target asset, may be included in a set of ordered assets based on the category of an anchor asset. Fill rates, total views of the target asset, or a combination may be used in selecting an optimization strategy. A dual optimization may be used to reduce the burden of presentation based on historical yield rates and follow-on rates observed from category transition data. Serendipity may be incorporated in the process through use of a reserve pool of transitions.

A method is disclosed. The method may include receiving real market data from a database; receiving user input data from a user device; retrieving a real-time current follower count for a user; determining at least one of an activity price per follower or an adjusted price per follower based on the retrieved real-time current follower count; generating an adjusted dataset by adjusting the filtered received real market data based on the determined at least one the price per follower or the adjusted price per follower; generating one or more match level tables by reducing the adjusted dataset based on one or more predetermined thresholds; generating a final dataset based on the generated one or more match level tables; and determining a suggested activity price for the user based on the generated final dataset.

A system and method for providing and synthesizing data for publishers operating in the connected television ecosystem. Data from third party reporting platforms may be combined to present a unified view. Audience engagement may be measured, observed, and combined in a novel manner, providing unique insights to users.

A method, apparatus and computer program product are provided for integrated sales management. A sales resource may use the system to track and modify promotion proposals for providers. Data defining the proposed promotion may include information relating to the provider, capacity, the promotion structure, return on investment, and/or an auto-approval status. Some data defining the proposed promotion may be automatically generated by the promotional system and/or modified by the provider. The proposal may be auto-approved or approved manually by a sales resource. Upon approval, the promotion may be made available for sale.