Dynamics on and of complex networks III : machine learning and statistical physics approaches
著者
書誌事項
Dynamics on and of complex networks III : machine learning and statistical physics approaches
（Springer proceedings in complexity）
Springer, c2019
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注記
Other editors: Rishiraj Saha Roy, Fariba Karimi, Jean-Charles Delvenne, Bivas Mitra
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
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