Automated ER Diagram Generation, Plagiarism Check and AI-Based Quiz System

Abstract

The proposed study covers a range of topics, including entity-relationship (ER) diagram analysis and extraction, plagiarism detection in ER diagrams, AI-based quiz systems, and database architecture and administration. The first section focuses on applying natural language processing to automate ER diagram development and SQL query formulation, possibly reducing time, and assisting non-technical users in database access and decision-making. The integrity of database systems is an issue; thus the second section provides a plagiarism detection component that contrasts visual and quantitative accuracy. The final section introduces an AI-based quiz system that fills in the gaps left by traditional quizzing techniques by providing individualized feedback, dynamically produced questions, and the capacity to assess text-based solutions. The last section describes the creation of a machine-learning model for precise entity recognition and attribute extraction from ER diagrams, offering a useful tool for academics. While filling in specific research gaps, this extensive study advances several fields, including database systems, AI-based teaching, and ER diagram analysis.