• DocumentCode
    3780120
  • Title

    The bio-inspired and social evolution of node and data in a multilayer network

  • Author

    Marialisa Scat?;Alessandro Di Stefano;Evelina Giacchi;Aurelio La Corte;Pietro Li?

  • Author_Institution
    Department of Electrical, Electronics and Computer Science Engineering, University of Catania, A. Doria 6 street, Catania, Italy
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Following a bio-inspired approach, applied to multilayer social networks, the idea is to build a novel paradigm aimed to improve methodologies and analysis in the Information and Communication Technologies. The social network and the multilayer structure allow to carry out an analysis of the complex patterns, in terms of the dynamics involving the main entities, nodes and data. The nodes represent the basic kernel from which generating ties, interactions, flow of information, influences and action strategies that affect the communities. The data, gathered from multiple sources, after their integration, will become complex objects, enclosing different kinds of information. The proposed approach introduces a level of abstraction that originates from the evolution of nodes and data transformed in “social objects”. This new paradigm consists of a multilayer social network, divided into three layers, generating an increasing awareness, from “things” to “knowledge”, extracting as much “knowledge” as possible. This paradigm allows to redesign the ICT in a bio-networks driven approach.
  • Keywords
    "Social network services","Nonhomogeneous media","Data mining","Diseases","Context","Object oriented modeling","Complexity theory"
  • Publisher
    ieee
  • Conference_Titel
    Data Communication Networking (DCNET), 2014 5th International Conference on
  • Type

    conf

  • Filename
    7509768