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Network Science : 7th International Winter Conference, NetSci-X 2022, Porto, Portugal, February 8-11, 2022, Proceedings / edited by Pedro Ribeiro, Fernando Silva, José Fernando Mendes, Rosário Laureano.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 13197
- Information Systems and Applications, incl. Internet/Web, and HCI ; 13197
- Language:
- English
- Subjects (All):
- Computer engineering.
- Computer networks.
- Application software.
- Social sciences-Data processing.
- Computer Engineering and Networks.
- Computer and Information Systems Applications.
- Computer Application in Social and Behavioral Sciences.
- Local Subjects:
- Computer Engineering and Networks.
- Computer and Information Systems Applications.
- Computer Application in Social and Behavioral Sciences.
- Physical Description:
- 1 online resource (XII, 185 pages) : 45 illustrations, 38 illustrations in color.
- Edition:
- 1st ed. 2022.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed proceedings of the 7th International Conference and School of Network Science, NetSci-X 2022, held in Porto, Portugal, in February 2021. The 13 full papers were carefully reviewed and selected from 19 submissions. The papers deal with the study of network models in domains ranging from biology and physics to computer science, from financial markets to cultural integration, and from social media to infectious diseases.
- Contents:
- Using localized attacks with probabilistic failures to model seismic events over physical-logical interdependent network
- A Historical Perspective On International Treaties Via Hypernetwork Science
- On the Number of Edges of the Frechet Mean and Median Graphs
- Core but not Peripheral Online Social Ties is a Protective Factor against Depression: Evidence from a Nationally Representative Sample of Young Adults
- Deep Topological Embedding with Convolutional Neural Networks for Complex Network Classification
- Modularity-based Backbone Extraction in Weighted Complex Networks
- Vessel destination prediction using a graph-based machine learning model
- Hunting for Dual-target Set on a Class of Hierarchical Networks
- Generalized Linear Models Network Autoregression
- Constructing Provably Robust Scale-free Networks
- Functional characterization of transcriptional regulatory networks of yeast species
- Competitive Information Spreading on Modular Networks
- HyperNetVec: Fast and Scalable Hierarchical Embedding for Hypergraphs.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-97240-0
- 9783030972400
- Access Restriction:
- Restricted for use by site license.
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