Comprehensive Review on Adaptive Natural Language Interfaces for Autonomous Relational Database Schema Synthesis and Context-Aware Query Interpretation Using Advanced NLP Techniques

Abstract

In this purposed system we provide a solution to a complex problem of building a system which can auto-matically create a database, populate it with data and re-spond to user queries. The system automatically creates a database based on user queries, and does entity extrac-tion, intent identification and automatically transforms nat-ural language input to SQL queries that can be executed on the database. The system also supports conversation and provides schema aware processing, supports query val-idation, and also includes data visualization. In order to provide these functionalities, we have integrated NLP tech-niques with state-of-the-art database systems. In addition, we have worked on multiple features that increase system performance. The main focus of this work has been to make database interactions easier for the users by reducing the gap between natural language and SQL. We have created a platform that supports all of these, and allows its users to provide inputs in natural language, and get results without having to write a line of SQL to interact with the database. This provides a scalable and efficient solution to manage data in various scenarios.