Reconstructing networks
Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with th...
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| Sprache: | English |
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Cambridge University Press
2021
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| Schriftenreihe: | Cambridge elemets. Elements in structure and dynamics of complex networks
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| 245 | 1 | 0 | |a Reconstructing networks |c Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini |
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| 520 | |a Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections. | ||
| 700 | 1 | |a Mastrandrea, Rossana | |
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| id | ZDB-20-CTM-CR9781108771030 |
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| isbn | 9781108771030 |
| issn | 2516-5763 |
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| series2 | Cambridge elemets. Elements in structure and dynamics of complex networks |
| spelling | Cimini, Giulio Reconstructing networks Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini Cambridge Cambridge University Press 2021 1 Online-Ressource (96 Seiten) txt c cr Cambridge elemets. Elements in structure and dynamics of complex networks 2516-5763 Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections. Mastrandrea, Rossana Squartini, Tiziano Erscheint auch als Druck-Ausgabe 9781108726818 TUM01 ZDB-20-CTM TUM_PDA_CTM https://doi.org/10.1017/9781108771030 Volltext |
| spellingShingle | Cimini, Giulio Reconstructing networks |
| title | Reconstructing networks |
| title_auth | Reconstructing networks |
| title_exact_search | Reconstructing networks |
| title_full | Reconstructing networks Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini |
| title_fullStr | Reconstructing networks Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini |
| title_full_unstemmed | Reconstructing networks Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini |
| title_short | Reconstructing networks |
| title_sort | reconstructing networks |
| url | https://doi.org/10.1017/9781108771030 |
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