Cohesive Subgraph Computation over Large Sparse Graphs - Algorithms, Data Structures, and Programming Techniques (Hardcover, 1st ed. 2018)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Series in the Data Sciences
Release date:	December 2018
First published:	2018
Authors:	Lijun Chang • Lu Qin
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	107
Edition:	1st ed. 2018
ISBN-13:	978-3-03-003598-3
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures
LSN:	3-03-003598-0
Barcode:	9783030035983

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