Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Amelia Zafra and Eva Gibaja and Sebastian Ventura",
  title =        "Multiple Instance Learning with MultiObjective Genetic
                 Programming for Web Mining",
  booktitle =    "Eighth International Conference on Hybrid Intelligent
                 Systems, HIS '08",
  year =         "2008",
  month =        sep,
  pages =        "513--518",
  keywords =     "genetic algorithms, genetic programming, G3P-MI, MIL,
                 MOG3P-MI, Web mining, grammar guided genetic
                 programming, k-nearest neighbour algorithm, multi
                 objective genetic programming, multiobjective grammar,
                 multiple instance learning, Internet, data mining,
                 learning (artificial intelligence)",
  DOI =          "doi:10.1109/HIS.2008.120",
  abstract =     "This paper introduces a multiobjective grammar based
                 genetic programming algorithm to solve a Web Mining
                 problem from multiple instance perspective. This
                 algorithm, called MOG3P-MI, is evaluated and compared
                 with other available algorithms which extend a
                 well-known neighborhood-based algorithm (k-nearest
                 neighbour algorithm) and with a mono objective version
                 of grammar guided genetic programming G3P-MI.
                 Computational experiments show that, the MOG3PMI
                 algorithm obtains the best results, solves problems of
                 k-nearest neighbour algorithms, such as sparsity and
                 scalability, adds comprehensibility and clarity in the
                 knowledge discovery process and overcomes the results
                 of single objective version.",
  notes =        "Also known as \cite{4626681}",

Genetic Programming entries for Amelia Zafra Gomez Eva L Gibaja Sebastian Ventura