Discovering Discriminant Characteristic Queries from Databases through Clustering

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

  title =        "Discovering Discriminant Characteristic Queries from
                 Databases through Clustering",
  author =       "Tae-wan Ryu and Christoph F. Eick",
  booktitle =    "Fourth International Conference on Computer Science
                 and Informatics (CS\&I'98)",
  year =         "1998",
  address =      "Research Triangle Park, NC, U.S.A.",
  month =        oct # " 23-28",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  citeseer-references = "oai:CiteSeerPSU:524488;
                 \cite{oai:CiteSeerPSU:45760}; oai:CiteSeerPSU:97771",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:190072",
  rights =       "unrestricted",
  abstract =     "this paper, we will describe a methodology and a set
                 of computerized tools that discover characteristic
                 queries as discriminant rules from structured
                 databases. In order to discover useful set of
                 discriminant characteristic queries from a database,
                 our approach is first to cluster the target database
                 and to discover a set of queries from each cluster.
                 Figure 1 depicts the overall steps in our methodology.
                 First, the input data set that user is interested in is
                 selected, preprocessed, and represented in a proper
                 format for clustering process. Second, generalized
                 clustering algorithms are then applied to the
                 preprocessed data set grouping the target database into
                 clusters of objects with similar properties. In the
                 third step, we try to characterize the clusters found
                 in the clustering process. For this purpose, we use a
                 query discovery system called MASSON that uses database
                 queries as its rule representation language [9]. MASSON
                 discovers a discriminant query (or set of queries) that
                 describes a given set of objects in databases using
                 genetic programming (GP) [4]. The discovered query or a
                 set of queries can distinctively describe the
                 commonalities for the given set of objects with respect
                 to the other objects in a database [8,10].",
  notes =        "Not verified: try also JCIS-98",

Genetic Programming entries for Tae-Wan Ryu Christoph F Eick