Abstract: Techniques and solutions are provided for encoding information for sets, including sets whose elements are arranged in a hierarchy. Values are defined for different levels of a hierarchy, where the values increase or decrease from a root of the hierarchy. A flattened representation of the hierarchy is generated by multiplying element values by a level value for a level at which a respective element is located. Values for parent and leaf nodes are defined, and a flattened representation of the hierarchy is generated by multiple elements values by the parent value or the leaf node value, depending on whether a respective elements is a parent or leaf node. Quantity values for a set of elements are encoded by adding a quantity of a given element to a value assigned to elements of a set definition that are present in a set.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: Techniques and solutions are provided for determining elements of a routing. A set of inputs is obtained, where the set of inputs includes sets of one or more characteristics for respective inputs of the set of inputs. At least a portion of values for the one or more characteristics are submitted along with a set of labels to train a machine learning model. A set of inference data that includes input values for a set of one or more characteristics for inputs of the set of inference data is analyzed using the machine learning model to provide an inference result. The inference result provides a predicted set of labels associated with a routing element of a routing involving the set of inference data. Using characteristics values can provide more accurate inference results and can allow a greater portion of data to be used as training data.

Abstract: Techniques and solutions are provided for encoding information for sets, including sets whose elements are arranged in a hierarchy. Values are defined for different levels of a hierarchy, where the values increase or decrease from a root of the hierarchy. A flattened representation of the hierarchy is generated by multiplying element values by a level value for a level at which a respective element is located. Values for parent and leaf nodes are defined, and a flattened representation of the hierarchy is generated by multiple elements values by the parent value or the leaf node value, depending on whether a respective elements is a parent or leaf node. Quantity values for a set of elements are encoded by adding a quantity of a given element to a value assigned to elements of a set definition that are present in a set.

Abstract: Techniques and solutions are provided for predicting elements of a routing. Such elements include processing resources used in processing a set of inputs, a sequence of processing resources used in processing a set of inputs, operations performed on the inputs, a sequence of the operations, standard values associated with the operations, and how inputs are allocated to processing resources or operations. A machine learning model is trained with a set of inputs and a set of labels for one or more elements of a routing. A set of inputs for inference data is provided to the trained model and a prediction for one of the routing elements is provided. For sequence information, training data can be used to generate a probability model which can be used to obtain an inferred sequence of processing resources or operations.

Abstract: Systems and methods are provided for digital assistant configuration and functionality. For example, systems and methods provide for receiving a query from a user via a computing device, processing language in the query to identify a plurality of elements associated with the query, and analyzing the plurality of elements associated with the query to determine an intent of the query by mapping the plurality of elements associated with the query to a list of predetermined intents by comparing the plurality of elements associated with the query to each intent in the list of predetermined intents to generate a score for each intent in the list of predetermined intents. Systems and methods further provide for determining a subset of the predetermined intents based on the score for each intent in the list of predetermined intents, and providing recommendations related to the query based on the subset of predetermined intents.

Abstract: Systems and methods are provided for receiving and processing a query to determine an intent of the query, and analyzing the intent of the query to determine that the intent of the query is associated with a use case state diagram. Systems and methods further provide for traversing a plurality of nodes in the user case state diagram to generate a value for each relevant node, performing an operation associated with the query using the generated values, and providing the results of the operation to a computing device.

Abstract: Systems and methods are provided for receiving a plurality of queries from plurality of channels via a plurality of computing devices. For each query of the plurality of queries systems and methods are provided for determining a use case associated with the query from a plurality of predetermined use cases, determining transformation rules for data associated with the use case, accessing data from at least one data source of a plurality of data sources to generate response data for a response to the query, the plurality of data sources comprising the data in a plurality of different data formats, transforming the data associated with the use case from at least a first format into a uniform data structure comprising the response data using the transformation rules for the response data, and providing the response data in the uniform data structure.

Abstract: Systems and methods are provided for receiving and processing a query to determine an intent of the query, and analyzing the intent of the query to determine that the intent of the query is associated with a use case state diagram. Systems and methods further provide for traversing a plurality of nodes in the user case state diagram to generate a value for each relevant node, performing an operation associated with the query using the generated values, and providing the results of the operation to a computing device.

Abstract: Systems and methods are provided for receiving and processing a query to determine an intent of the query, and analyzing the intent of the query to determine that the intent of the query is associated with a use case state diagram. Systems and methods further provide for traversing a plurality of nodes in the user case state diagram to generate a value for each relevant node, performing an operation associated with the query using the generated values, and providing the results of the operation to a computing device.

Abstract: Systems and methods are provided for digital assistant configuration and functionality. For example, systems and methods provide for receiving a query from a user via a computing device, processing language in the query to identify a plurality of elements associated with the query, and analyzing the plurality of elements associated with the query to determine an intent of the query by mapping the plurality of elements associated with the query to a list of predetermined intents by comparing the plurality of elements associated with the query to each intent in the list of predetermined intents to generate a score for each intent in the list of predetermined intents. Systems and methods further provide for determining a subset of the predetermined intents based on the score for each intent in the list of predetermined intents, and providing recommendations related to the query based on the subset of predetermined intents.

Abstract: Systems and methods are provided for receiving and processing a query to determine an intent of the query, and analyzing the intent of the query to determine that the intent of the query is associated with a use case state diagram. Systems and methods further provide for traversing a plurality of nodes in the user case state diagram to generate a value for each relevant node, performing an operation associated with the query using the generated values, and providing the results of the operation to a computing device.

Abstract: Systems and methods are provided for receiving a plurality of queries from plurality of channels via a plurality of computing devices For each query of the plurality of queries systems and methods are provided for determining a use case associated with the query from a plurality of predetermined use cases, determining transformation rules for data associated with the use case, accessing data from at least one data source of a plurality of data sources to generate response data for a response to the query, the plurality of data sources comprising the data in a plurality of different data formats, transforming the data associated with the use case from at least a first format into a uniform data structure comprising the response data using the transformation rules for the response data, and providing the response data in the uniform data structure

Abstract: Embodiments of systems, methods, and computer-readable mediums for analysis of datasets without predefined dimensions are generally described herein. In some embodiments, analysis of datasets without predefined dimensions may include receiving a selection of multiple dimensions of information from a database to be used for data analysis; receiving a selection for a type of report; and dynamically generating a query statement based on the selection of the multiple dimensions. Further embodiments may include the dynamically generated query statement including multiple iterative join clauses as a function of the selected dimensions; executing the query statement against an in-memory database; and displaying columns of information obtained from execution of the query statement.

Abstract: The present invention is directed to a one piece blank of foldable sheet material cut and scored so that it is divided into a series of connected wall forming panels which when assembled provides an oval folding carton with an automatic closing bottom for packaging an article. The present invention is also directed to a one piece oval shaped carton with an automatic closing bottom for packaging an article.

Abstract: The present invention is directed to a one piece blank of foldable sheet material cut and scored so that it is divided into a series of connected wall forming panels which when assembled provides an oval folding carton with an automatic closing bottom for packaging an article. The present invention is also directed to a one piece oval shaped carton with an automatic closing bottom for packaging an article.

Abstract: The present invention is directed to a one piece blank of foldable sheet material cut and scored so that it is divided into a series of connected wall forming panels which when assembled provides a trio of diamond shaped cartons for packaging articles, each carton connected to another carton by a common edge. The present invention is also directed to a one piece trio of diamond shaped cartons for packaging articles, each carton connected to another carton by a common edge.