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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| Hauptverfasser: | , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2021
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 TUM01 URL des Erstveröffentlichers |
| Zusammenfassung: | 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 |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 18 Aug 2021) |
| Beschreibung: | 1 Online-Ressource (96 Seiten) |
| ISBN: | 9781108771030 |
| DOI: | 10.1017/9781108771030 |
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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 | ||
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Datensatz im Suchindex
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| author | Cimini, Giulio 1984- Mastrandrea, Rossana ca. 20./21. Jh Squartini, Tiziano 1983- |
| author_GND | (DE-588)1242046453 (DE-588)124204745X (DE-588)1242046925 |
| author_facet | Cimini, Giulio 1984- Mastrandrea, Rossana ca. 20./21. Jh Squartini, Tiziano 1983- |
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| author_sort | Cimini, Giulio 1984- |
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| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 003 - Systems |
| dewey-raw | 003 |
| dewey-search | 003 |
| dewey-sort | 13 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1017/9781108771030 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:14:26Z |
| indexdate | 2024-07-10T09:13:27Z |
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| isbn | 9781108771030 |
| language | English |
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| spelling | Cimini, Giulio 1984- (DE-588)1242046453 aut Reconstructing networks Giulio Cimini, Rossana Mastrandrea, Tiziano Squartini Cambridge Cambridge University Press 2021 1 Online-Ressource (96 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 18 Aug 2021) 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 System analysis Network analysis (Planning) Information theory Statistical physics Mastrandrea, Rossana ca. 20./21. Jh. (DE-588)124204745X aut Squartini, Tiziano 1983- (DE-588)1242046925 aut Erscheint auch als Druck-Ausgabe 978-1-108-72681-8 https://doi.org/10.1017/9781108771030 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Cimini, Giulio 1984- Mastrandrea, Rossana ca. 20./21. Jh Squartini, Tiziano 1983- Reconstructing networks System analysis Network analysis (Planning) Information theory Statistical physics |
| title | Reconstructing networks |
| title_auth | Reconstructing networks |
| title_exact_search | Reconstructing networks |
| title_exact_search_txtP | 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 |
| topic | System analysis Network analysis (Planning) Information theory Statistical physics |
| topic_facet | System analysis Network analysis (Planning) Information theory Statistical physics |
| url | https://doi.org/10.1017/9781108771030 |
| work_keys_str_mv | AT ciminigiulio reconstructingnetworks AT mastrandrearossana reconstructingnetworks AT squartinitiziano reconstructingnetworks |