Complex Networks & Their Applications VI : Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications) (Studies in Computational Intelligence)

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Complex Networks & Their Applications VI : Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications) (Studies in Computational Intelligence)

Cherifi, Chantal (EDT)/ Cherifi, Hocine (EDT)/ Karsai, Márton (EDT)

ウェブストア価格 ¥69,228（本体¥62,935）
Springer International Publishing AG（2018/09発売）
外貨定価 US$ 329.99
ポイント 629pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 1288 p.
言語 ENG
商品コード 9783319891491
DDC分類 006.3

Full Description

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the VI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2017), which took place in Lyon on November 29 - December 1, 2017. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and ecological networks and technological networks.

Part I: Network measures.- A comparison of approaches to computing betweenness centrality for large graphs.- Cycle-centrality in economic and biological networks.- A game theoretic neighbourhood-based relevance index.- The impact of partially missing communities on the reliability of centrality measures.- Consistent estimation of mixed memberships with successive projections.- Reducing pivots of approximated betweenness computation by hierarchically clustering complex networks.- Power network equivalents: a network science based k-means clustering method integrated with silhouette analysis.- Part II: Link Analysis and Ranking.- Newton's gravitational law for link prediction in social networks.- Efﬁcient outlier detection in hyperedge streams using minHash and locality-sensitive hashing.- Layer-wise model stacking for link prediction in multilayer networks. Case of scientiﬁc collaboration networks.- Evolutionary community mining for link prediction in dynamic networks.- Rank aggregation for course sequence discovery.- Part III: Community Structure.- Community-based feature selection for credit card default prediction.- Tracking bitcoin users activity using community detection on a network of weak signals.