• DocumentCode
    1790967
  • Title

    Pheromone base swarm approach for Detecting articulation user node in social networking

  • Author

    Sanadhya, Shashvat ; Agrawal, Nidhi ; Singh, Sushil

  • Author_Institution
    Dept. of CEA, NITTTR, Bhopal, India
  • fYear
    2014
  • fDate
    12-13 July 2014
  • Firstpage
    461
  • Lastpage
    465
  • Abstract
    Modern world is living in the `aeon´ of virtual community, where people connect to each other through any kind of relationship. Social networking is platform where people share emotions, activities, area of interest etc. Communities in social network are deployed in user nodes with connecting people, it may seem that there is some user which is common among many communities. These user node is a kind of `social articulation points (SAP)´ which is like a bridge between communities. In this paper with the help of `ant colony optimization´ (ACO) we are proposing `pheromone based swarm approach for articulation user´ (PSAP) to find articulation user point in a social network. ACO is meta-heuristic which helps to solve combinational problems such as TSP, Graph color, job shop Network routing, machine learning etc. Hence social networking may be a new platform with ant colony optimization, to solve complex task in social phenomena.
  • Keywords
    ant colony optimisation; combinatorial mathematics; social sciences; ACO; PSAP; SAP; TSP; ant colony optimization; articulation user node detection; combinational problems; graph color; job shop network routing; machine learning; meta-heuristic; pheromone base swarm approach; social articulation points; social networking; social phenomena; user nodes; virtual community; Cities and towns; Context; Instruments; Signal processing algorithms; ACO; SAP; Swarm-Intelligence; user rank matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Propagation and Computer Technology (ICSPCT), 2014 International Conference on
  • Conference_Location
    Ajmer
  • Print_ISBN
    978-1-4799-3139-2
  • Type

    conf

  • DOI
    10.1109/ICSPCT.2014.6884910
  • Filename
    6884910