Conceptual Clustering Applied to Ontologies by means of Semantic Discernability

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@InProceedings{Esposito:2007:PriCKL,
  author =       "Floriana Esposito and Nicola Fanizzi and 
                 Claudia d'Amato",
  title =        "Conceptual Clustering Applied to Ontologies by means
                 of Semantic Discernability",
  booktitle =    "ECML/PKDD Workshop on Prior Conceptual Knowledge in
                 Machine Learning and Knowledge Discovery, PriCKL'07",
  year =         "2007",
  address =      "Warsaw, Poland",
  month =        sep # " 21",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.ecmlpkdd2007.org/CD/workshops/PRICKLWM2/P_Fan/PriCKL07/PriCkl2007-final.pdf",
  abstract =     "A clustering method is presented which can be applied
                 to relational knowledge bases to discover interesting
                 groupings of resources through their annotations
                 expressed in the standard languages of the Semantic
                 Web. The method exploits a simple (yet effective and
                 language-independent) semi-distance measure for
                 individuals, that is based on the semantics of the
                 resources w.r.t. a number of dimensions corresponding
                 to a set of concept descriptions (discriminating
                 features). The algorithm adapts the classic BISECTING
                 K-MEANS to work with medoids. A final experiment
                 demonstrates the validity of the approach using
                 absolute quality indices",
  notes =        "Says based on GP and Simulated Annealing

                 Dipartimento di Informatica, Universit`a degli Studi di
                 Bari Campus Universitario, Via Orabona 4, 70125 Bari,
                 Italy",
}

Genetic Programming entries for Floriana Esposito Nicola Fanizzi Claudia d'Amato

Citations