000 -LEADER |
fixed length control field |
a |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
191120b xxu||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783319694368 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
621 |
Item number |
SQU |
100 ## - MAIN ENTRY--PERSONAL NAME |
Personal name |
Squartini, Tiziano |
245 ## - TITLE STATEMENT |
Title |
Maximum-entropy networks : pattern detection, network reconstruction and graph combinatorics |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc |
Cham |
Name of publisher, distributor, etc |
Springer |
Date of publication, distribution, etc |
2017 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xii, 116 p. |
Other physical details |
ill. |
Dimensions |
24 cm. |
365 ## - TRADE PRICE |
Unit of pricing |
54.99 |
Price amount |
EUR |
Price type code |
82.00 |
490 ## - SERIES STATEMENT |
Series statement |
SpringerBriefs in complexity |
Volume number/sequential designation |
2191-5326 |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references and index.
|
520 ## - SUMMARY, ETC. |
Summary, etc |
This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties. After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem of network reconstruction and introduces various advanced techniques to reliably infer the topology of a network from partial local information. Chapter 5 is devoted to the reformulation of certain "hard" combinatorial operations, such as the enumeration and unbiased sampling of graphs with given constraints, within a "softened" maximum-entropy framework. A final chapter offers various overarching remarks and take-home messages. By requiring no prior knowledge of network theory, the book targets a broad audience ranging from PhD students approaching these topics for the first time to senior researchers interested in the application of advanced network techniques to their field. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Random graphs |
|
Topical term or geographic name as entry element |
System analysis |
|
Topical term or geographic name as entry element |
System theory |
|
Topical term or geographic name as entry element |
Cybernetics and systems theory |
|
Topical term or geographic name as entry element |
Maximum entropy method |
|
Topical term or geographic name as entry element |
Applications of Graph Theory and Complex Networks |
|
Topical term or geographic name as entry element |
Statistical Physics and Dynamical Systems |
|
Topical term or geographic name as entry element |
Graph theory |
|
Topical term or geographic name as entry element |
Computational complexity |
|
Topical term or geographic name as entry element |
Complex Systems |
710 ## - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
Garlaschelli, Diego |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
|
Item type |
Books |