A guide to temporal networks:
"Network science offers a powerful language to represent and study complex systems composed of interacting elements -- from the Internet to social and biological systems. In its standard formulation, this framework relies on the assumption that the underlying topology is static, or changing ver...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London
World Scientific Publishing Europe Ltd.
2020
|
| Ausgabe: | 2nd edition |
| Schriftenreihe: | Series on complexity science
vol. 6 |
| Schlagworte: | |
| Online-Zugang: | UPA01 URL des Erstveröffentlichers |
| Zusammenfassung: | "Network science offers a powerful language to represent and study complex systems composed of interacting elements -- from the Internet to social and biological systems. In its standard formulation, this framework relies on the assumption that the underlying topology is static, or changing very slowly as compared to dynamical processes taking place on it, e.g., epidemic spreading or navigation. Fuelled by the increasing availability of longitudinal networked data, recent empirical observations have shown that this assumption is not valid in a variety of situations. Instead, often the network itself presents rich temporal properties and new tools are required to properly describe and analyse their behaviour. A Guide to Temporal Networks presents recent theoretical and modelling progress in the emerging field of temporally varying networks, and provides connections between different areas of knowledge required to address this multi-disciplinary subject. After an introduction to key concepts on networks and stochastic dynamics, the authors guide the reader through a coherent selection of mathematical and computational tools for network dynamics. Perfect for students and professionals, this book is a gateway to an active field of research developing between the disciplines of applied mathematics, physics and computer science, with applications in others including social sciences, neuroscience and biology"-- |
| Beschreibung: | 1 Online-Ressource (300 Seiten) Illustrationen |
| ISBN: | 9781786349163 9781786349170 |
| DOI: | 10.1142/q0268 |
Internformat
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Datensatz im Suchindex
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| author | Masuda, Naoki 1976- |
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| author_sort | Masuda, Naoki 1976- |
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| bvnumber | BV047022052 |
| classification_rvk | ST 650 ST 630 |
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| ctrlnum | (OCoLC)1225885422 (DE-599)BVBBV047022052 |
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| dewey-search | 003 |
| dewey-sort | 13 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1142/q0268 |
| edition | 2nd edition |
| format | Electronic eBook |
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| id | DE-604.BV047022052 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T15:59:30Z |
| indexdate | 2024-07-10T09:00:23Z |
| institution | BVB |
| isbn | 9781786349163 9781786349170 |
| language | English |
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| series2 | Series on complexity science |
| spelling | Masuda, Naoki 1976- Verfasser (DE-588)1124619283 aut A guide to temporal networks Naoki Masuda, Renaud Lambiotte 2nd edition London World Scientific Publishing Europe Ltd. 2020 1 Online-Ressource (300 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier Series on complexity science vol. 6 "Network science offers a powerful language to represent and study complex systems composed of interacting elements -- from the Internet to social and biological systems. In its standard formulation, this framework relies on the assumption that the underlying topology is static, or changing very slowly as compared to dynamical processes taking place on it, e.g., epidemic spreading or navigation. Fuelled by the increasing availability of longitudinal networked data, recent empirical observations have shown that this assumption is not valid in a variety of situations. Instead, often the network itself presents rich temporal properties and new tools are required to properly describe and analyse their behaviour. A Guide to Temporal Networks presents recent theoretical and modelling progress in the emerging field of temporally varying networks, and provides connections between different areas of knowledge required to address this multi-disciplinary subject. After an introduction to key concepts on networks and stochastic dynamics, the authors guide the reader through a coherent selection of mathematical and computational tools for network dynamics. Perfect for students and professionals, this book is a gateway to an active field of research developing between the disciplines of applied mathematics, physics and computer science, with applications in others including social sciences, neuroscience and biology"-- System analysis Computational complexity Social networks / Mathematical models Electronic books Netzwerk (DE-588)4171529-9 gnd rswk-swf Dynamik (DE-588)4013384-9 gnd rswk-swf Netzwerk (DE-588)4171529-9 s Dynamik (DE-588)4013384-9 s DE-604 Lambiotte, Renaud Sonstige (DE-588)1124849483 oth Erscheint auch als Druck-Ausgabe 978-1-78634-915-6 https://doi.org/10.1142/q0268 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Masuda, Naoki 1976- A guide to temporal networks System analysis Computational complexity Social networks / Mathematical models Electronic books Netzwerk (DE-588)4171529-9 gnd Dynamik (DE-588)4013384-9 gnd |
| subject_GND | (DE-588)4171529-9 (DE-588)4013384-9 |
| title | A guide to temporal networks |
| title_auth | A guide to temporal networks |
| title_exact_search | A guide to temporal networks |
| title_exact_search_txtP | A guide to temporal networks |
| title_full | A guide to temporal networks Naoki Masuda, Renaud Lambiotte |
| title_fullStr | A guide to temporal networks Naoki Masuda, Renaud Lambiotte |
| title_full_unstemmed | A guide to temporal networks Naoki Masuda, Renaud Lambiotte |
| title_short | A guide to temporal networks |
| title_sort | a guide to temporal networks |
| topic | System analysis Computational complexity Social networks / Mathematical models Electronic books Netzwerk (DE-588)4171529-9 gnd Dynamik (DE-588)4013384-9 gnd |
| topic_facet | System analysis Computational complexity Social networks / Mathematical models Electronic books Netzwerk Dynamik |
| url | https://doi.org/10.1142/q0268 |
| work_keys_str_mv | AT masudanaoki aguidetotemporalnetworks AT lambiotterenaud aguidetotemporalnetworks |