Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: Example aspects include techniques for query processing over deep neural network runtimes. These techniques include receiving a query including a query operator and a trainable user defined function (UDF). In addition, the techniques include determining a query representation based on the query, and determining, for performing the query in a neural network runtime, an initial neural network program based on the query representation, the initial neural network program including a differentiable operators corresponding to the query operator. and executing the neural network program in the neural network runtime over the neural network data structure to generate a query result. Further, the techniques include training the initial neural network program via the neural network runtime to determine a trained neural network program, and executing the trained neural network program in the neural network runtime to generate inference information.

Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: Linguistic schema mapping via semi-supervised learning is used to map a customer schema to a particular industry-specific schema (ISS). The customer schema is received and a corresponding ISS is identified. An attribute in the customer schema is selected for labeling. Candidate pairs are generated that include the first attribute and one or more second attributes which may describe the first attribute. A featurizer determines similarities between the first attribute and second attribute in each generated pair, one or more suggested labels are generated by a machine learning (ML) model, and one of the suggested labels is applied to the first attribute.

Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: Example aspects include techniques for query processing over deep neural network runtimes. These techniques may include receiving a query including one or more query operators and determining a query representation based on the one or more query operators. In addition, the techniques may include determining a neural network program based on the query representation, the neural network program including one or more neural network operators for performing the query in a neural network runtime, generating a neural network data structure based on a dataset associated with the query, and executing the neural network program in the neural network runtime over the neural network data structure to generate a query result.