Dr. Bhargavi Konda

AI driven Data Mining techniques in IT

Abstract:

Data mining has long been a fundamental technique in the field of information technology, enabling organizations to extract meaningful patterns, insights, and correlations from vast datasets. With the advent of artificial intelligence (AI), traditional data mining methods have been significantly transformed, enhancing automation, accuracy, and scalability. This report explores AI-driven data mining techniques, including machine learning, deep learning, reinforcement learning, and federated learning, highlighting their role in modern IT applications. The study begins with an overview of traditional data mining methods such as classification, clustering, association rule mining, and anomaly detection, illustrating their foundational role in data analysis. It then delves into the evolution of AI-powered approaches, showcasing advanced techniques like neural networks, graph neural networks (GNNs), and AutoML, which have revolutionized data extraction, pattern recognition, and predictive modeling. Furthermore, key AI algorithms such as decision trees, support vector machines (SVMs), random forests, and deep learning models (CNNs, RNNs, Transformers) are analyzed in detail. The applications of AI-driven data mining are explored across critical IT domains, including cybersecurity, fraud detection, customer behavior analysis, healthcare IT, and financial market prediction. Real-world case studies, such as AI-powered threat detection, predictive maintenance, and e-commerce personalization, further illustrate the practical implications of AI-enhanced data mining. Finally, the talk addresses the challenges and future trends associated with AI in data mining, including scalability, ethical considerations, AI explainability, and the emergence of technologies such as Edge AI and Explainable AI (XAI). As AI continues to evolve, its integration with data mining is expected to drive innovation and efficiency, shaping the future of intelligent data analysis in IT."