Network science : 7th International Winter Conference, NetSci-X 2022, Porto, Portugal, February 8-11, 2022 : proceedings
著者
書誌事項
Network science : 7th International Winter Conference, NetSci-X 2022, Porto, Portugal, February 8-11, 2022 : proceedings
(Lecture notes in computer science, 13197)
Springer, c2022
- : [pbk.]
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
"LNCS sublibrary: SL3 - Information systems and applications, incl. Internet/Web, and HCI"--T.p. verso
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
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.
「Nielsen BookData」 より