A flexible framework for multiple-role discovery in real networks

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Vydáno v:Applied Network Science Ročník 7
Hlavní autoři: Shu Liu, Fujio Toriumi, Mao Nishiguchi, Shohei Usui
Médium: Journal Article
Jazyk:angličtina
japonština
Vydáno: Springer Science and Business Media LLC 01.12.2022
Témata:
Adversarial learning
Applied mathematics. Quantitative methods
Community extraction
Complex network
Multi-label classification
Real network
Role discovery
T57-57.97
ISSN:2364-8228
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Author Mao Nishiguchi
Fujio Toriumi
Shu Liu
Shohei Usui
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SubjectTerms Adversarial learning
Applied mathematics. Quantitative methods
Community extraction
Complex network
Multi-label classification
Real network
Role discovery
T57-57.97
Title A flexible framework for multiple-role discovery in real networks
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