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Dynamics On and Of Complex Networks III = Machine Learning and Statistical Physics Approaches /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Dynamics On and Of Complex Networks III/ edited by Fakhteh Ghanbarnejad, Rishiraj Saha Roy, Fariba Karimi, Jean-Charles Delvenne, Bivas Mitra.
其他題名:	Machine Learning and Statistical Physics Approaches /
其他作者:	Ghanbarnejad, Fakhteh.
面頁冊數:	X, 244 p. 76 illus., 68 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Sociophysics. -
電子資源:	https://doi.org/10.1007/978-3-030-14683-2
ISBN:	9783030146832

Dynamics On and Of Complex Networks III = Machine Learning and Statistical Physics Approaches /
Dynamics On and Of Complex Networks IIIMachine Learning and Statistical Physics Approaches /[electronic resource] :edited by Fakhteh Ghanbarnejad, Rishiraj Saha Roy, Fariba Karimi, Jean-Charles Delvenne, Bivas Mitra. - 1st ed. 2019. - X, 244 p. 76 illus., 68 illus. in color.online resource. - Springer Proceedings in Complexity,2213-8684. - Springer Proceedings in Complexity,.

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. .

This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical 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.

ISBN: 9783030146832

Standard No.: 10.1007/978-3-030-14683-2doiSubjects--Topical Terms:

890761
Sociophysics.

LC Class. No.: QC1-999

Dewey Class. No.: 621

Dynamics On and Of Complex Networks III = Machine Learning and Statistical Physics Approaches /
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