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[null,null,"Titolo",null,"Dynamics On and Of Complex Networks III : Machine Learning and Statistical Physics Approaches / / edited by Fakhteh Ghanbarnejad, Rishiraj Saha Roy, Fariba Karimi, Jean-Charles Delvenne, Bivas Mitra"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019"]
[null,null,"ISBN",null,"3-030-14683-9"]
[null,null,"Edizione",null,"[1st ed. 2019.]"]
[null,null,"Descrizione fisica",null,"1 online resource (225 pages)"]
[null,null,"Collana",null,"Springer Proceedings in Complexity, , 2213-8692"]
[null,null,"Disciplina",null,"005.8"]
[{"$nulls":4},"004.6"]
[null,null,"Soggetti",null,"System theory"]
[{"$nulls":4},"Dynamics"]
[{"$nulls":4},"Nonlinear theories"]
[{"$nulls":4},"Sociology - Methodology"]
[{"$nulls":4},"Complex Systems"]
[{"$nulls":4},"Applied Dynamical Systems"]
[{"$nulls":4},"Sociological Methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Part1. Network Structure -- Chapter1. An Empirical Study of the Effect of Noise Models on Centrality Metrics -- Chapter2. Emergence and Evolution of Hierarchical Structure in Complex Systems -- Chapter3. Evaluation of Cascading Infrastructure Failures and Optimal Recovery from a Network Science Perspective -- Part2. Network Dynamics -- Chapter4. Automatic Discovery of Families of Network Generative Processes -- Chapter5. Modeling User Dynamics in Collaboration Websites -- Chapter6. The Problem of Interaction Prediction in Link Streams -- Chapter7. The Network Source Location Problem in the Context of Foodborne Disease Outbreaks -- Part3. Theoretical Models and applications -- Chapter8. Network Representation Learning using Local Sharing and Distributed Graph Factorization (LSDGF) -- Chapter9. The Anatomy of Reddit: An Overview of Academic Research -- Chapter10. Learning Information Dynamics in Social Media: A Temporal Point Process Perspective. ."]
[null,null,null,"Sommario/riassunto","This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical "]
[{"$nulls":4},"physics. It contains diverse but relevant topics in statistical physics, complex systems, network theory, and machine learning. Examples of such topics are: predicting missing links, higher-order generative modeling of networks, inferring network structure by tracking the evolution and dynamics of digital traces, recommender systems, and diffusion processes. The book contains extended versions of high-quality submissions received at the workshop, Dynamics On and Of Complex Networks (doocn.org), together with new invited contributions. The chapters will benefit a diverse community of researchers. The book is suitable for graduate students, postdoctoral researchers and professors of various disciplines including sociology, physics, mathematics, and computer science."]