Mining association rules with single and multi-objective grammar guided ant programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Juan Luis Olmo and Jose Maria Luna and 
                 Jose Raul Romero and Sebastian Ventura",
  title =        "Mining association rules with single and
                 multi-objective grammar guided ant programming",
  journal =      "Integrated Computed-Aided Engineering",
  year =         "2013",
  volume =       "20",
  number =       "3",
  pages =        "217--234",
  keywords =     "genetic algorithms, genetic programming, Ant
                 programming, ant colony optimisation, multi-objective
                 optimisation, association rule mining, data mining",
  DOI =          "doi:10.3233/ICA-130430",
  size =         "18 pages",
  abstract =     "This paper treats the first approximation to the
                 extraction of association rules by employing ant
                 programming, a technique that has recently reported
                 very promising results in mining classification rules.
                 In particular, two different algorithms are presented,
                 both guided by a context-free grammar that defines the
                 search space, specifically suited to association rule
                 mining. The first proposal follows a single-objective
                 approach in which a novel fitness function is used to
                 evaluate the individuals mined. In contrast, the second
                 algorithm considers individual evaluation from a
                 Pareto-based point of view, measuring the confidence
                 and support of the rules mined and assigning them a
                 ranking fitness. Both algorithms are verified over 16
                 varied data sets, comparing their results to other
                 association rule mining algorithms from several
                 paradigms such as exhaustive search, genetic
                 algorithms, and genetic programming. The results
                 obtained are very promising, and they indicate that ant
                 programming is a good technique for the association
                 task of data mining, lacking of the drawbacks that
                 exhaustive methods present.",

Genetic Programming entries for Juan Luis Olmo Jose Maria Luna Jose Raul Romero Salguero Sebastian Ventura