The complex networks science has recently attracted much attention from the scientific community, mainly due to the pervasive presence of complex phenomena in real-world systems such as peer-to-peer systems, social networks, and communication networks. Understanding complex networks and simplifying complex phenomena in them for practitioners is a very challenging task, where many well-established disciplines, like machine learning, data mining, and graph theory, have found great applications in the recent years to give insights into such complex networks. Building on the success in the past four years, the Fifth Annual Workshop on Simplifying Complex Networks for Practitioners – SIMPLEX 2013 continues to serve as a forum for researcher s as well as practitioners to disseminate and discuss recent advances and emerging issues in understanding and simplifying complex networks.
Proceedings of the Workshop on Simplifying Complex Networks for Practitioners (SIMPLEX 2013)
FERRETTI, STEFANO;
2013
Abstract
The complex networks science has recently attracted much attention from the scientific community, mainly due to the pervasive presence of complex phenomena in real-world systems such as peer-to-peer systems, social networks, and communication networks. Understanding complex networks and simplifying complex phenomena in them for practitioners is a very challenging task, where many well-established disciplines, like machine learning, data mining, and graph theory, have found great applications in the recent years to give insights into such complex networks. Building on the success in the past four years, the Fifth Annual Workshop on Simplifying Complex Networks for Practitioners – SIMPLEX 2013 continues to serve as a forum for researcher s as well as practitioners to disseminate and discuss recent advances and emerging issues in understanding and simplifying complex networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
