This book provides a thorough introduction to graph mining and addresses foundational concepts and advanced techniques along with practical applications across various fields.  As graphs have become increasingly vital for data representation in domains such as social network analysis, bioinformatics, and transportation, there is a growing demand for a comprehensive source that covers both theory and practical insights. This book seeks to fill that gap by offering clear explanations, practical examples, and actionable insights, making complex graph mining techniques accessible to students, postgraduate readers, and researchers.  The authors also provide an extensive investigation into the process of gaining insightful knowledge from graph representations, ranging from interpreting intricate relationships to decoding complex data structures.  Readers will learn to identify anomalous patterns, locate communities, arrange nodes, predict connections, and evaluate graphs effectively.

This book provides a thorough introduction to graph mining and addresses foundational concepts and advanced techniques along with practical applications across various fields.  As graphs have become increasingly vital for data representation in domains such as social network analysis, bioinformatics, and transportation, there is a growing demand for a comprehensive source that covers both theory and practical insights. This book seeks to fill that gap by offering clear explanations, practical examples, and actionable insights, making complex graph mining techniques accessible to students, postgraduate readers, and researchers.  The authors also provide an extensive investigation into the process of gaining insightful knowledge from graph representations, ranging from interpreting intricate relationships to decoding complex data structures.  Readers will learn to identify anomalous patterns, locate communities, arrange nodes, predict connections, and evaluate graphs effectively.

This book provides a thorough introduction to graph mining and addresses foundational concepts and advanced techniques along with practical applications across various fields.  As graphs have become increasingly vital for data representation in domains such as social network analysis, bioinformatics, and transportation, there is a growing demand for a comprehensive source that covers both theory and practical insights. This book seeks to fill that gap by offering clear explanations, practical examples, and actionable insights, making complex graph mining techniques accessible to students, postgraduate readers, and researchers.  The authors also provide an extensive investigation into the process of gaining insightful knowledge from graph representations, ranging from interpreting intricate relationships to decoding complex data structures.  Readers will learn to identify anomalous patterns, locate communities, arrange nodes, predict connections, and evaluate graphs effectively.