Graph Mining

Practical Uses and Instruments for Exploring Complex Networks
Herausgegeben:Bhattacharya, Riju; Rathore, Yogesh Kumar; Tran, Tien Anh; Swarnkar, Suman Kumar

• Gebundenes Buch

Produktbeschreibung

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.

Produktdetails

• Synthesis Lectures on Computer Science
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-93801-6
• Seitenzahl: 165
• Erscheinungstermin: Juli 2025
• Englisch
• Abmessung: 240mm x 168mm
• ISBN-13: 9783031938016
• Artikelnr.: 73891352

Inhaltsangabe

Graph Mining: Power Laws and Graph Queries.- Frequent Subgraphs Mining.- Analyzing and Predicting Links in Graph-Based Data.- Node Similarity and Classification.- Graph Classification.- Graph Clustering.- Overlapping and Non-overlapping Communities.- Anomaly Detection.- Graph Summarization.- Knowledge Graph Processing.- Role of Deep Learning in Graph Mining.- Graph Convolutional Network (GCN).