• DocumentCode
    501329
  • Title

    Research on Multi-Relational Classification Approaches

  • Author

    Zhen Peng ; Wu, Lifeng ; Wang, Xiaoju

  • Author_Institution
    Dept. of Comput., North China Inst. of Sci. & Technol., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    51
  • Lastpage
    54
  • Abstract
    As an important task of multi-relational data mining, multi-relational classification can directly look for patterns that involve multiple relations from a relational database and have more advantages than propositional data mining approaches. According to the differences in knowledge representation and strategy, the paper researched three kind of multi-relational classification approaches that are ILP based, graph-based and relational database-based classification approaches and discussed each relational classification technology, their characteristics, the comparisons and several challenging researching problems in detail.
  • Keywords
    data mining; graph theory; inductive logic programming; knowledge representation; pattern classification; relational databases; ILP based classification; graph-based classification; inductive logic programming; knowledge representation; multirelational classification; multirelational data mining; relational database-based classification; Classification tree analysis; Computational intelligence; Data mining; Decision trees; Electronic mail; Knowledge representation; Logic programming; Relational databases; Telecommunication computing; Testing; Inductive Logic Programming (ILP); Multi-relational data mining; graph; multi-relational classification; selection graph; tuple ID propagation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.166
  • Filename
    5231577