• DocumentCode
    424238
  • Title

    Information query immune algorithm based on vector space model

  • Author

    Wang, Zi-qiang ; Feng, Bo-Qin

  • Author_Institution
    Dept. of Comput. Sci., Xi´´an Jiaotong Univ., China
  • Volume
    4
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    2515
  • Abstract
    To efficiently satisfy the user query requirements in information retrieval, a novel immune query optimization algorithm for information retrieval is proposed. The core of the immune algorithm lies on constructing the immune operator that is realized by vaccination and immune selection. The strategies and the methods of selecting and constructing a vaccine for the problem are given in the paper. Immune algorithm for query optimization introduces the immune operators to genetic algorithms for query optimization. This algorithm properly deals with the degeneration in conventional genetic algorithms, therefore increases the convergence speed. Experimental results show that the novel algorithm has higher precision and faster computation speed.
  • Keywords
    genetic algorithms; information retrieval; genetic algorithm; immune query optimization algorithm; information query immune algorithm; information retrieval; query optimization; query requirement; vaccination; vector space model; Computer science; Evolution (biology); Genetic algorithms; Immune system; Information retrieval; Machine learning; Machine learning algorithms; Neural networks; Optimization methods; Query processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1382227
  • Filename
    1382227