Induction of linear genetic programs for relational database manipulation   [GP]

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Archanjo, G., A. and Zuben, F., J., V.

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Info: IEEE International Conference on Information Reuse and Integration (IRI 2011) (Conference proceedings), 2011, p. 347-352
Keywords:genetic algorithms, genetic programming, KDD, Knowledge Discovery, Data Mining, LGPDB, Linear Genetic Programming for Databases, hypothetical library system, relational database management system, data mining, relational databases
Abstract:
In virtually all fields of human activity, softwares are used to manage processes and manipulate information, usually stored in computer databases. In fields like Knowledge Discovery [KD] and Data Mining (KDD), different approaches [DM] have been used to extract patterns or more meaningful information from datasets, including genetic programming. [GP] Nevertheless, the induction [IOP] of programs that not only query data, but also manipulate it, has not been widely explored. This work presents Linear Genetic Programming [LGP] [GP] for Databases (LGPDB), a tool to induce programs manipulating entities stored in a relational database. It combines a Linear Genetic Programming (LGP) induction environment [LGP] [GP] and a simple relational database management system (RDBMS). A hypothetical library system [HLS] is used to show LGPDB in action. Programs were induced to provide a set of selected features for this system and results indicate that genetic programming [GP] can be used to model processes that query, delete, insert and update records in a relational database.
Notes:
Also known as cite{6009572}
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BibTex:
@InProceedings{Archanjo:2011:IRI,
  author =       "Gabriel A. Archanjo and Fernando J. {Von Zuben}",
  title =        "Induction of linear genetic programs for relational
                 database manipulation",
  booktitle =    "IEEE International Conference on Information Reuse and
                 Integration (IRI 2011)",
  year =         "2011",
  month =        "3-5 " # aug,
  pages =        "347--352",
  address =      "Las Vegas, USA",
  size =         "6 pages",
  abstract =     "In virtually all fields of human activity, softwares
                 are used to manage processes and manipulate
                 information, usually stored in computer databases. In
                 fields like Knowledge Discovery and Data Mining (KDD),
                 different approaches have been used to extract patterns
                 or more meaningful information from datasets, including
                 genetic programming. Nevertheless, the induction of
                 programs that not only query data, but also manipulate
                 it, has not been widely explored. This work presents
                 Linear Genetic Programming for Databases (LGPDB), a
                 tool to induce programs manipulating entities stored in
                 a relational database. It combines a Linear Genetic
                 Programming (LGP) induction environment and a simple
                 relational database management system (RDBMS). A
                 hypothetical library system is used to show LGPDB in
                 action. Programs were induced to provide a set of
                 selected features for this system and results indicate
                 that genetic programming can be used to model processes
                 that query, delete, insert and update records in a
                 relational database.",
  keywords =     "genetic algorithms, genetic programming, KDD,
                 Knowledge Discovery and Data Mining, LGPDB, Linear
                 Genetic Programming for Databases, hypothetical library
                 system, relational database management system, data
                 mining, relational databases",
  doi =          "doi:10.1109/IRI.2011.6009572",
  notes =        "Also known as cite{6009572}",
}