Dell Products Inc.

Dell & Products L.p.

Sailendu Kumar Patra

Saurabh Jha

Guhesh Swaminathan

Priya Shanmugasundaram

Kuruba Ajay Kumar

Shweta Goyal

Kailash Talreja

Srishti Gupta

A method for training a model to generate a structured query language (SQL) output using a natural language input includes receiving a training data set that includes natural language queries, corresponding SQL statements, and a corresponding database. The method also includes extracting query-specific schema from the corresponding database. Further, the method includes embedding the natural language queries and the query-specific schema to generate initialized embeddings, where each initialized embedding corresponds to a natural language query of the natural language queries, and where the corresponding SQL statement is one of the corresponding SQL statements; generating subgraphs based on the initialized embeddings and the natural language queries; training a graph neural network (GNN) using the subgraphs as inputs; generating, using the GNN, refined outputs based on the subgraphs; and training a transformer model using the refined outputs and the natural language queries to obtain a trained model.

Contextual graph dynamics for natural language to SQL conversion

Methods, apparatus, and processor-readable storage media for automated address data determinations using artificial intelligence techniques are provided herein. An example computer-implemented method includes extracting address information from one or more documents using at least one artificial intelligence-based address extraction model; parsing, into one or more address components, at least a portion of the extracted address information using at least one artificial intelligence-based parsing model; comparing at least a portion of the one or more parsed address components to stored address information using at least one artificial intelligence-based scoring model; and performing one or more automated actions based at least in part on results from the comparing of at least a portion of the one or more parsed address components to stored address information.

Automated address data determinations using artificial intelligence techniques

A method for automatically responding to a user input includes receiving the user input. The method also includes identifying a current domain associated with the user input. Further, the method includes determining, using a previously trained learning model, a first belief state, where the first belief state is based on the current domain. In addition, the method includes determining, using a reinforcement learning model, a second belief state, where the second belief state is based on the current domain and a reward information. Moreover, the method includes determining an action based on the user input and one selected from the group consisting of the first belief state and the second belief state. Also, the method includes generating a response based on the action and presenting the response to a user.

Method and system to automatically respond to a user input

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Bengaluru, India

Sailendu Kumar Patra