• DocumentCode
    2580097
  • Title

    Wise mining method through ant colony optimization

  • Author

    Jianxiong, Yang ; Watada, Junzo

  • Author_Institution
    Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    1833
  • Lastpage
    1839
  • Abstract
    This paper proposes an algorithm for data mining named Pheromone-Miner (ant-colony-based data miner). The algorithm is inspired by both researches on the behavior of real ant colonies and data mining concepts as well as principles. The goal of Pheromone-Miner is to extract more exact knowledge from a database. Pheromone-based mining breaks through limitations of other mining approaches. We compare the performance of pheromone-miner with a general semantic miner. The accident causes discovered by ant-miner are considerably more accurate than those discovered by a general semantic miner. In a word, this evolutionary algorithm is suitable for improving the accuracy of data miners.
  • Keywords
    data mining; optimisation; Pheromone-Miner; ant colony optimization; ant-colony-based data miner; data mining; evolutionary algorithm; general semantic miner; knowledge extraction; wise mining method; Ant colony optimization; Clustering algorithms; Cybernetics; Data mining; Databases; Electronic mail; Insects; Production systems; Robustness; USA Councils; ant colony optimization algorithm; data mining; knowledge discovery; pheromone;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2793-2
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2009.5346807
  • Filename
    5346807