| 书目名称 | Maximum-Entropy Networks |
| 副标题 | Pattern Detection, N |
| 编辑 | Tiziano Squartini,Diego Garlaschelli |
| 视频video | |
| 概述 | A complete self-consistent introduction to a general methodology to study complex networks.Emphasizes the connections between pattern detection, network reconstruction and graph combinatorics.Includes |
| 丛书名称 | SpringerBriefs in Complexity |
| 图书封面 |  |
| 描述 | 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 refor |
| 出版日期 | Book 2017 |
| 关键词 | Complex Networks; Maximum-entropy Ensembles; Maximum likelihood estimation; Undirected networks; Directe |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-69438-2 |
| isbn_softcover | 978-3-319-69436-8 |
| isbn_ebook | 978-3-319-69438-2Series ISSN 2191-5326 Series E-ISSN 2191-5334 |
| issn_series | 2191-5326 |
| copyright | The Author(s) 2017 |
发表于 2025-3-21 19:38:06
