• DocumentCode
    3507709
  • Title

    Ant Colony Optimization and Data Mining: Techniques and Trends

  • Author

    Michelakos, Ioannis ; Mallios, Nikolaos ; Papageorgiou, Elpiniki ; Vassilakopoulos, Michael

  • Author_Institution
    Dept. of Comput. Sci. & Biomed. Inf., Univ. of Central Greece, Lamia, Greece
  • fYear
    2010
  • fDate
    4-6 Nov. 2010
  • Firstpage
    284
  • Lastpage
    289
  • Abstract
    The Ant Colony Optimization (ACO) technique was inspired by the ants´ behaviour throughout their exploration for food. The use of this technique has been very successful for several problems. Besides, Data Mining (DM) has emerged as an important technology with numerous practical applications, due to the wide availability of a vast amount of data. The collaborative use of ACO and DM is very promising. In this paper, we review ACO, DM, Classification and Clustering (popular DM tasks) and focus on the use of ACO for Classification and Clustering. Moreover, we briefly present related applications and examples and outline possible future trends of this promising collaborative use of techniques.
  • Keywords
    data mining; optimisation; pattern classification; pattern clustering; ant colony optimization; data mining; pattern classification; pattern clustering; Ant Colony Optimization (ACO); Classification; Clustering; Data Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2010 International Conference on
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-1-4244-8538-3
  • Electronic_ISBN
    978-0-7695-4237-9
  • Type

    conf

  • DOI
    10.1109/3PGCIC.2010.47
  • Filename
    5662775