Statistical Analysis of Networks
This book is a general introduction to the statistical analysis of networks, and can serve both as a research monograph and as a textbook. Numerous fundamental tools and concepts needed for the analysis of networks are presented, such as network modeling, community detection, graph-based semi-superv...
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| Hoofdauteurs: | , |
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| Formaat: | Online |
| Taal: | Engels |
| Gepubliceerd in: |
Now Publishers
2023
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| Onderwerpen: | |
| Online toegang: | https://library.oapen.org/handle/20.500.12657/60497 |
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| _version_ | 1869517065326428160 |
|---|---|
| author | Avrachenkov, Konstantin Dreveton, Maximilien |
| author_browse | Avrachenkov, Konstantin Dreveton, Maximilien |
| author_facet | Avrachenkov, Konstantin Dreveton, Maximilien |
| author_sort | Avrachenkov, Konstantin |
| collection | Directory of Open Access Books |
| description | This book is a general introduction to the statistical analysis of networks, and can serve both as a research monograph and as a textbook. Numerous fundamental tools and concepts needed for the analysis of networks are presented, such as network modeling, community detection, graph-based semi-supervised learning and sampling in networks. The description of these concepts is self-contained, with both theoretical justifications and applications provided for the presented algorithms.
Researchers, including postgraduate students, working in the area of network science, complex network analysis, or social network analysis, will find up-to-date statistical methods relevant to their research tasks. This book can also serve as textbook material for courses related to the
statistical approach to the analysis of complex networks.
In general, the chapters are fairly independent and self-supporting, and the book could be used for course composition “à la carte”. Nevertheless, Chapter 2 is needed to a certain degree for all parts of the book. It is also recommended to read Chapter 4 before reading Chapters 5 and 6, but this is not absolutely necessary. Reading Chapter 3 can also be helpful before reading Chapters 5 and 7.
As prerequisites for reading this book, a basic knowledge in probability, linear algebra and elementary notions of graph theory is advised. Appendices describing required notions from the above mentioned disciplines have been added to help readers gain further understanding. |
| format | Online |
| id | doab-20.500.12854ir-95753 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Now Publishers |
| publisherStr | Now Publishers |
| record_format | ojs |
| spelling | doab-20.500.12854ir-957532025-08-13T13:42:18Z Statistical Analysis of Networks Avrachenkov, Konstantin Dreveton, Maximilien Network analysis, statistical analysis, network modeling, community detection, graph-based semi-supervised learning, sampling in networks Textbook thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols This book is a general introduction to the statistical analysis of networks, and can serve both as a research monograph and as a textbook. Numerous fundamental tools and concepts needed for the analysis of networks are presented, such as network modeling, community detection, graph-based semi-supervised learning and sampling in networks. The description of these concepts is self-contained, with both theoretical justifications and applications provided for the presented algorithms. Researchers, including postgraduate students, working in the area of network science, complex network analysis, or social network analysis, will find up-to-date statistical methods relevant to their research tasks. This book can also serve as textbook material for courses related to the statistical approach to the analysis of complex networks. In general, the chapters are fairly independent and self-supporting, and the book could be used for course composition “à la carte”. Nevertheless, Chapter 2 is needed to a certain degree for all parts of the book. It is also recommended to read Chapter 4 before reading Chapters 5 and 6, but this is not absolutely necessary. Reading Chapter 3 can also be helpful before reading Chapters 5 and 7. As prerequisites for reading this book, a basic knowledge in probability, linear algebra and elementary notions of graph theory is advised. Appendices describing required notions from the above mentioned disciplines have been added to help readers gain further understanding. 2023-01-05T04:02:17Z 2023-01-05T04:02:17Z 2023-01-04T13:04:04Z 2022 book https://library.oapen.org/handle/20.500.12657/60497 9781638280507 https://directory.doabooks.org/handle/20.500.12854/95753 eng NowOpen open access image/jpeg image/jpeg image/jpeg Attribution-NonCommercial 4.0 International Attribution-NonCommercial 4.0 International Attribution-NonCommercial 4.0 International https://library.oapen.org/bitstream/20.500.12657/60497/1/9781638280514.pdf https://library.oapen.org/bitstream/20.500.12657/60497/1/9781638280514.pdf https://library.oapen.org/bitstream/20.500.12657/60497/1/9781638280514.pdf Now Publishers 10.1561/9781638280514 10.1561/9781638280514 53ae8601-d009-4a47-bfed-73b89c40b091 9781638280507 237 open access |
| spellingShingle | Network analysis, statistical analysis, network modeling, community detection, graph-based semi-supervised learning, sampling in networks Textbook thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols Avrachenkov, Konstantin Dreveton, Maximilien Statistical Analysis of Networks |
| title | Statistical Analysis of Networks |
| title_full | Statistical Analysis of Networks |
| title_fullStr | Statistical Analysis of Networks |
| title_full_unstemmed | Statistical Analysis of Networks |
| title_short | Statistical Analysis of Networks |
| title_sort | statistical analysis of networks |
| topic | Network analysis, statistical analysis, network modeling, community detection, graph-based semi-supervised learning, sampling in networks Textbook thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols |
| topic_facet | Network analysis, statistical analysis, network modeling, community detection, graph-based semi-supervised learning, sampling in networks Textbook thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols thema EDItEUR::U Computing and Information Technology::UT Computer networking and communications::UTP Networking standards and protocols |
| url | https://library.oapen.org/handle/20.500.12657/60497 |
| work_keys_str_mv | AT avrachenkovkonstantin statisticalanalysisofnetworks AT drevetonmaximilien statisticalanalysisofnetworks |