Cohesive Subgraph Computation over Large Sparse Graphs

1. Front Matter

   Pages i-xii

   PDF

2. Introduction

   • Lijun Chang, Lu Qin

   Pages 1-8

3. Linear Heap Data Structures

   • Lijun Chang, Lu Qin

   Pages 9-20

4. Minimum Degree-Based Core Decomposition

   • Lijun Chang, Lu Qin

   Pages 21-39

5. Average Degree-Based Densest Subgraph Computation

   • Lijun Chang, Lu Qin

   Pages 41-53

6. Higher-Order Structure-Based Graph Decomposition

   • Lijun Chang, Lu Qin

   Pages 55-75

7. Edge Connectivity-Based Graph Decomposition

   • Lijun Chang, Lu Qin

   Pages 77-98

8. Back Matter

   Pages 99-107

   PDF

This book is considered the first extended survey on algorithms and techniques for efficient cohesive subgraph computation. With rapid development of information technology, huge volumes of graph data are accumulated. An availability of rich graph data not only brings great opportunities for realizing big values of data to serve key applications, but also brings great challenges in computation. Using a consistent terminology, the book gives an excellent introduction to the models and algorithms for the problem of cohesive subgraph computation. The materials of this book are well organized from introductory content to more advanced topics while also providing well-designed source codes for most algorithms described in the book.
 
This is a timely book for researchers who are interested in this topic and efficient data structure design for large sparse graph processing. It is also a guideline book for new researchers to get to know the area of cohesive subgraph computation.

• Cohesive Subgraph Computation
• K-Core
• Densest Subgraph
• K-Edge Connected Component
• Maximum Clique
• data structures

• School of Computer Science, The University of Sydney, Sydney, Australia

  Lijun Chang

• Centre for Artificial Intelligence, University of Technology Sydney, Sydney, Australia

  Lu Qin

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