Atnaujinkite slapukų nuostatas

El. knyga: Complex Networks & Their Applications IX: Volume 1, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020

Edited by , Edited by , Edited by , Edited by , Edited by , Edited by

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

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 IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). 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 neuroscience networks and technological networks. 

 


Structural Node Embedding in Signed Social Networks: Finding Online
Misbehavior at Multiple Scales.- On the Impact of Communities on
Semi-supervised Classication Using Graph Neural Networks.- Detecting
Geographical Competitive Structure for POI Visit Dynamics.- Graph
Convolutional Network with Time-based Mini-batch for Information Diusion
Prediction.- Experimental Evaluation of Train and Test Split Strategies in
Link Prediction.- Incorporating Domain Knowledge into Health Recommender
Systems Using Hyperbolic Embeddings.- Learning Parameters for Balanced Index
Inuence Maximization.- Connecting the Dots: Integrating Point Location Data
into Spatial Network Analyses.- Topological Analysis of Synthetic Models for
Air Transportation Multilayer Networks.- Extending DeGroot Opinion Formation
for Signed Graphs and Minimising Polarization.- Forming Diverse Teams Based
on Members Social Networks: A Genetic Algorithm Approach.