Abstract: Systems and methods for identifying item substitutions. History information can be collected. The history information can be transformed into a matrix of observed substitutions. A neural network can be trained on the matrix of observed substitutions to generate item embeddings. A substitution similarity between the item and another item based on the item embeddings can be identified.

Abstract: Methods, systems, and computer storage media for providing an optimal control configuration for a material processing system are provided. In operation, a material processing engine accesses causal graph input data. Causal graph input data includes input data of a continuous flow process. Based on the causal graph and the input data, a causal graph that aligns with do-calculus manipulations—associated with determining identifiable causal relationships corresponding to input materials of the continuous flow process—is generated. The causal graph is parsed based on the do-calculus manipulations to determine valid conditioning sets associated with estimating a causal impact on an optimization target. Based on the valid conditioning sets, an optimal control configuration comprising optimal control variable values is generated.

Abstract: Systems and methods are disclosed for displaying information related to items in a store. Stock keeping unit (SKU) information for items in the store and combination information indicating which SKUs were sold together can be determined.

Abstract: Methods, systems, and computer storage media for providing an error remediation recommendation—for flagged incorrect values in broadband service deployment data—using a broadband error remediation engine in a data analytics system. The error remediation recommendation can identify a corrective action to resolve errors (i.e., incorrect values) in broadband service deployment data. Operationally, the broadband error remediation engine is configured to access broadband service deployment data associated with a plurality of broadband service data features. The broadband error remediation engine uses an error remediation model to and a plurality of datasets to execute a sequence of error remediation operations (e.g., checks and comparisons). Based on executing the sequence of error remediation operations, a corrective action (e.g., change geographic coordinates or remove deployment units) for an incorrect value of a broadband service feature in the broadband service deployment data.

Abstract: Systems and methods for identifying item substitutions. History information can be collected. The history information can be transformed into a matrix of observed substitutions. A neural network can be trained on the matrix of observed substitutions to generate item embeddings. A substitution similarity between the item and another item based on the item embeddings can be identified.

Abstract: Methods and Systems for context-sensitive manipulation of an object via a presentation software are disclosed.

Abstract: Systems and methods for identifying item substitutions. History information can be collected. The history information can include one or more episodes from one or more customers. Each episode can include one or more items. The history information can be transformed into a matrix of observed substitutions. A neural network can be trained on the matrix of observed substitutions to generate item embeddings. Input including an item can be received. A substitution similarity between the item and another item based on the item embeddings can be identified.

Abstract: Systems and methods for managing data. Person and position data can be copied from a database and it can be determined whether a person is aligned to any positions. Information can be displayed representing the person and indicating any positions to which the person is aligned.

Abstract: A method for screening documents. The order of the text in the documents can be changed in order to create additional documents. A vocabulary of words from the text in the documents can be built. The words can be coded as vectors. Vector relationships can be defined. The documents can be classified using the vector relationships.

Abstract: Systems and methods for managing data. Person and position data can be copied from a database and it can be determined whether a person is aligned to any positions. Information can be displayed representing the person and indicating any positions to which the person is aligned.

Abstract: Methods and systems for determining relevance for a new document are described. Existing documents that have a high probability of relevance can be chosen. A vocabulary of words in the existing documents can be built. Each word can be mapped into a vector such that each existing document can be represented by a sequence of vectors and each sentence and/or paragraph in each existing document can be represented by a subsequence of vectors including a subset of the sequence of vectors. Data augmentation can be applied changing an order of the subsequences in order to create additional documents represented by the subsequences. A deep neural network can be trained using the subsequences that represent the existing documents and the subsequences that represent additional documents. The new documents can be trained using a trained deep neural network. A relevant document can be output using the trained deep neural network.

Abstract: Methods and systems of using reinforcement learning to optimizing promotions. A promotion can be offered to a user using a reinforcement learning model with a sensitivity parameter, the reinforcement module estimating a time period during which the user will respond to the first information. The user's reaction to the promotion can be observed. The reinforcement learning model can be adapted based on the user's reaction.

Abstract: Methods and systems for context-sensitive manipulation of an object via a presentation software are disclosed. A target object state can be obtained. An actual state of the object can be determined to be different from the target object state. The actual state of the object can be manipulated to synchronize with the target object state.

Abstract: Systems and methods for identifying item substitutions. History information can be collected. The history information can include one or more episodes from one or more customers. Each episode can include one or more items. The history information can be transformed into a matrix of observed substitutions. A neural network can be trained on the matrix of observed substitutions to generate item embeddings. Input including an item can be received. A substitution similarity between the item and another item based on the item embeddings can be identified. The item embeddings can be clustered to generate need states.

Abstract: Methods and systems of using reinforcement learning for promotions. A first promotion is offered to a customer for a product and/or service. A first reward or penalty is determined, via a reinforcement machine learning model, based on the customer's reaction to the first promotion, wherein the reinforcement machine learning model is at a first state. Feedback to the reinforcement machine learning model is provided based on the first reward or penalty. A state of the reinforcement machine learning model is changed, based on the feedback, from the first state to a second state.

Abstract: Methods and Systems for context-sensitive manipulation of an object via a presentation software are disclosed.

Abstract: Methods and Systems for using reinforcement learning to optimize promotions. A promotion can be offered to a customer for a prepaid calling card using a reinforcement learning model with a sensitivity parameter. The reinforcement learning model can estimate a time period during which the customer will purchase the prepaid calling card. The customer's reaction to the promotion can be observed. A reward or a penalty can be collected based on the customer's reaction. The reinforcement learning model can be adapted based on the reward or the penalty to optimize the timing of the promotion by estimating a new time period during which the customer will purchase the prepaid calling card. The reward proxy and/or the penalty proxy can comprise frequency of usage.

Abstract: Methods and systems for using reinforcement learning to optimizing promotions. A promotion for a product and/or service is offered to a customer using a reinforcement learning model. The customer's reaction is observed. A reward or a penalty is collected based on the customer's reaction. The reinforcement learning model is adapted based on the reward or penalty.

Abstract: Systems and methods are disclosed for displaying information related to items in a store. Stock keeping unit (SKU) information for items in the store and combination information indicating which SKUs were sold together can be accepted. Dimension information and structure information for a neural network can be defined. The neural network can be trained using the combination information indicating which SKUs were sold together in a same combination to calculate weight values and bias values for the neural network.

Abstract: Systems and methods are disclosed for displaying information related to items in a store. Stock keeping unit (SKU) information for items in the store and combination information indicating which SKUs were sold together can be determined.