Del 689 - Studies in Computational Intelligence

Complex Networks & Their Applications VI

Proceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications)

Häftad, Engelska, 2018

Av Chantal Cherifi, Hocine Cherifi, Márton Karsai, Mirco Musolesi, Marton Karsai

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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.

Produktinformation

Utgivningsdatum2018-09-07
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieStudies in Computational Intelligence
Antal sidor1 288
FörlagSpringer International Publishing AG
ISBN9783319891491

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Artificiell intelligens inom Data och it

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.