• DocumentCode
    2917594
  • Title

    An artificial immune system model for knowledge extraction and representation

  • Author

    Romero, Andres ; Nino, Fernando ; Quintana, Gerardo

  • Author_Institution
    Dept. of Comput. Eng., Nat. Univ. of Colombia, Bogota
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    3413
  • Lastpage
    3420
  • Abstract
    This paper presents an approach to knowledge extraction and representation based on an artificial immune system. The main idea is to extract the important concepts from a set of text documents, and find the relations between such concepts. At the end, a graph representation is obtained, which is intended to present a picture of the documentspsila contents. Some experiments were carried out in order to validate the proposed approach, and very promising results were obtained.
  • Keywords
    artificial immune systems; document handling; graph theory; knowledge representation; text analysis; artificial immune system model; graph representation; knowledge extraction; knowledge representation; text documents; Artificial immune systems; Association rules; Bibliographies; Data mining; Immune system; Information filtering; Information filters; Ontologies; Proposals; Visual databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631259
  • Filename
    4631259