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

-15% su kodu: ENG15
71,98 
Įprasta kaina: 84,68 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
71,98 
Įprasta kaina: 84,68 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 84.6800 InStock
Nemokamas pristatymas į paštomatus per 11-15 darbo dienų užsakymams nuo 20,00 

Knygos aprašymas

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.

Informacija

Autorius: Lu Qin, Lijun Chang,
Serija: Springer Series in the Data Sciences
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2019
Knygos puslapių skaičius: 120
ISBN-10: 3030035980
ISBN-13: 9783030035983
Formatas: 241 x 160 x 13 mm. Knyga kietu viršeliu
Kalba: Anglų

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