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Cohesive Subgraph Computation over Large Sparse Graphs: Algorithms, Data Structures, and Programming
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Cohesive Subgraph Computation over Large Sparse Graphs: Algorithms, Data Structures, and Programming

Cohesive Subgraph Computation over Large Sparse Graphs: Algorithms, Data Structures, and Programming

Lijun / Qin Chang

107 pages, parution le 06/01/2019

Résumé

This book is considered the first extended survey on algorithms and techniques for efficient cohesive subgraph computation.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.
Introduction.- Linear Heap Data Structures.- Minimum Degree-based Core Decomposition.- Average Degree-based Densest Subgraph Computation.- Higher-order Structure-based Graph Decomposition.- Edge Connectivity-based Graph Decomposition.

Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) Lijun / Qin Chang
Parution 06/01/2019
Nb. de pages 107
EAN13 9783030035983

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