• DocumentCode
    1897625
  • Title

    Study on Recommendation Algorithm Based on Artificial Immune Network

  • Author

    Lu, Lu ; Sui Jianjun

  • Author_Institution
    Fac. of Comput., Guangdong Univ. of Technol., Guangzhou, China
  • Volume
    2
  • fYear
    2012
  • fDate
    23-25 March 2012
  • Firstpage
    95
  • Lastpage
    98
  • Abstract
    A recommendation algorithm based on artificial immune network is proposed to deal with the problems of data sparsity and scalability in recommendation technology in the paper. The algorithm can reduce data sparsity and improve the accuracy by using its own mechanisms for dynamic regulation of the immune. The experimental results show that the algorithm has improved the recommend accuracy and has some practical significance.
  • Keywords
    artificial immune systems; data mining; recommender systems; artificial immune network; data scalability; data sparsity; recommendation algorithm; Accuracy; Algorithm design and analysis; Cloning; Data mining; Immune system; Prediction algorithms; Training; aiNet; immune network; recommendation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-0689-8
  • Type

    conf

  • DOI
    10.1109/ICCSEE.2012.399
  • Filename
    6187973
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1897625