Practical Graph Intelligence 2 delivers a comprehensive and application driven exploration of graph-based methods for understanding complex, interconnected data.
This book bridges theory and practice by presenting advanced techniques in graph theory, graph neural networks and network analytics, with a strong focus on real-world implementation. It addresses critical challenges such as scalability, interpretability and dynamic data handling while showcasing applications across healthcare, cybersecurity, social networks and smart systems.
Designed for researchers, practitioners and advanced students, this book highlights emerging trends and practical frameworks that enable efficient, data-driven decision-making. By integrating cutting-edge research with hands-on perspectives, it serves as a valuable resource for developing robust and intelligent graph-based solutions in today’s data intensive environments.
