On the Use of Ant Programming for Mining Rare Association Rules

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Olmo:2013:nabic,
  author =       "Juan Luis Olmo Ortiz and Jose-Raul Romero and 
                 Sebastian Ventura",
  title =        "On the Use of Ant Programming for Mining Rare
                 Association Rules",
  booktitle =    "5th World Congress on Nature and Biologically Inspired
                 Computing",
  year =         "2013",
  editor =       "Simone Ludwig and Patricia Melin and Ajith Abraham and 
                 Ana Maria Madureira and Kendall Nygard and 
                 Oscar Castillo and Azah Kamilah Muda and Kun Ma and 
                 Emilio Corchado",
  pages =        "220--225",
  address =      "Fargo, USA",
  month =        "12-14 " # aug,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, Data Mining,
                 Rare Association Rule Mining, Ant Programming",
  isbn13 =       "978-1-4799-1415-9",
  URL =          "http://www.mirlabs.net/nabic13/proceedings/html/paper52.xml",
  DOI =          "doi:10.1109/NaBIC.2013.6617866",
  size =         "6 pages",
  abstract =     "Most researches in association rule mining have
                 focused on the extraction of frequent and reliable
                 associations. However, there is an increasing interest
                 in finding reliable rules that rarely appear, and
                 recently, some classical solutions have been adapted to
                 this field. The problem is that most of these
                 algorithms follow an exhaustive approach, which have
                 the drawback of becoming unfeasible when dealing with
                 high complex data sets. This kind of problem can be
                 also addressed as an optimisation problem, for which
                 bio-inspired algorithms have proved their ability. To
                 this end, this paper presents an ant-based automatic
                 programming method for discovering rare association
                 rules. This algorithm lacks the drawbacks of exhaustive
                 approaches, having also some advantages, such as the
                 employment of a context-free grammar that allows to
                 adapt the algorithm to a particular domain. Results
                 show that this proposal can mine a set of reliable
                 infrequent rules in a short period of time.",
  notes =        "UCI USB only?, IEEE Catalog Number: CFP1395H-POD Also
                 known as \cite{6617866}",
}

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

Citations