• DocumentCode
    2326216
  • Title

    Extracting symbolic objects from relational databases

  • Author

    Stéphan, Véronique

  • Author_Institution
    Inst. Nat. de Recherche en Inf. et Autom., Le Chesnay, France
  • fYear
    1996
  • fDate
    9-10 Sep 1996
  • Firstpage
    514
  • Lastpage
    519
  • Abstract
    Our aim is to define operators to retrieve groups of individuals from a relational database. The way we describe these groups makes it possible to analyse them by symbolic data analysis methods which extend classical ones to more complex data. In so far as the input consists of groups of data extensionally defined in the database, our problem is to find the best description representing each group in the formalism (called symbolic object) of symbolic data analysis. In our process, we take into account data from tables together with additional knowledge such as taxonomies. To describe each group, we perform a generalization step and a specialization one. Final descriptions are based on the notion of homogeneity within a group and they minimize a volume criterion
  • Keywords
    data analysis; data description; database theory; generalisation (artificial intelligence); knowledge acquisition; query processing; relational databases; complex data; data description; data mining; generalization; group homogeneity; operators; relational databases; specialization; symbolic data analysis; symbolic object extraction; tables; taxonomies; volume criterion; Active appearance model; Data analysis; Data mining; Information analysis; Relational databases; Sampling methods; Statistical analysis; Taxonomy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications, 1996. Proceedings., Seventh International Workshop on
  • Conference_Location
    Zurich
  • Print_ISBN
    0-8186-7662-0
  • Type

    conf

  • DOI
    10.1109/DEXA.1996.558606
  • Filename
    558606