Network Algorithms, Data Mining, and Applications, 1st ed. 2020 NET, Moscow, Russia, May 2018 Springer Proceedings in Mathematics & Statistics Series, Vol. 315
Coordonnateurs : Bychkov Ilya, Kalyagin Valery A., Pardalos Panos M., Prokopyev Oleg
Introduces state-of-the-art techniques in computer science and network analysis
Features new theoretical models and approaches for network analysis with new efficient tools
Presents a range of application for network models and network analysis
Date de parution : 02-2021
Ouvrage de 244 p.
15.5x23.5 cm
Date de parution : 02-2020
Ouvrage de 244 p.
15.5x23.5 cm
Thème de Network Algorithms, Data Mining, and Applications :
Mots-clés :
Network algorithms; Clusters; Information Theory; graph dissimilarities; Metaheuristics; Large-Scale Graph Clustering; Traveling Salesman Problem; Link Partitioning; Partitioning Around Medoids; modeling clique relaxations; Integer programming techniques; Network Science Applications; Large-Scale Graph Processing Systems; Network data mining; Machine Learning Analysis; Gaussian graphical model; combinatorics