• DocumentCode
    1841805
  • Title

    Extended MRI-Cube Algorithm for Mining Multi-Relational Patterns

  • Author

    Liang, Bao ; Hong, Xiaoguang ; Zhang, Lei ; Li, Shuai

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Shandong Univ.
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    1132
  • Lastpage
    1136
  • Abstract
    Association rule mining is one of the most important and basic technique in data mining, which has been studied extensively and has a wide range of applications. Two stream of previous work has dealt with the discovery of association rules over multiple relations: prolog databases and datalog queries. The MRI Iceberg-cubes mining method introduces a new perspective. However, it does not take the cyclic join paths into account, therefore, in this paper, we will introduce an algorithm, Extended-MRI-cube, which is based on the MRI-Cube algorithm, to handle the cyclic join path situation. Experiments show it is more applicable and effective than the previous one.
  • Keywords
    data mining; graph theory; query processing; relational databases; association rule mining; cyclic join path algorithm; data mining; datalog query; extended multi relational iceberg-cube algorithm; multi relational pattern mining; prolog database; Application software; Association rules; Computer science; Data analysis; Data mining; Database systems; Logic programming; Partitioning algorithms; Relational databases; Scalability; Data mining; association rules; bottom up computation; multi-relational patterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.165
  • Filename
    4709133