A Flexible Knowledge Discovery System using Genetic Programming and Logic Grammars

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Wong:2001:DSS,
  author =       "Man Leung Wong",
  title =        "A Flexible Knowledge Discovery System using Genetic
                 Programming and Logic Grammars",
  journal =      "Decision Support Systems",
  year =         "2001",
  volume =       "31",
  pages =        "405--428",
  keywords =     "genetic algorithms, genetic programming, Knowledge
                 Discovery in Databases, Logic Grammars, Fuzzy Petri
                 Nets",
  URL =          "http://cptra.ln.edu.hk/~mlwong/journal/dss2001.pdf",
  URL =          "http://www.sciencedirect.com/science/article/B6V8S-43W051G-2/2/e504e5d59385b792e3c424bd5bb4d003",
  DOI =          "doi:10.1016/S0167-9236(01)00092-6",
  abstract =     "As the computing world moves from the information age
                 into the knowledge-based age, it is beneficial to
                 induce knowledge from the information super highway
                 formed from the Internet and intranet. The knowledge
                 acquired can be expressed in different knowledge
                 representations such as computer programs, first-order
                 logical relations, or Fuzzy Petri Nets (FPNs). In this
                 paper, we present a flexible knowledge discovery system
                 called GGP (Generic Genetic Programming) that applies
                 genetic programming and logic grammars to learn
                 knowledge in various knowledge representation
                 formalisms. An experiment is performed to demonstrate
                 that GGP can discover knowledge represented in FPNs
                 that support fuzzy and approximate reasoning. To
                 evaluate the performance of GGP in producing good FPNs,
                 the classification accuracy of the fuzzy Petri net
                 induced by GGP and that of the decision tree generated
                 by C4.5 are compared. Moreover, the performance of GGP
                 in inducing logic programs from noisy examples is
                 evaluated. A detailed comparison to FOIL, a system that
                 induces logic programs, has been conducted. These
                 experiments demonstrate that GGP is a promising
                 alternative to other knowledge discovery systems and
                 sometimes is superior for handling noisy and inexact
                 data.",
}

Genetic Programming entries for Man Leung Wong

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