• DocumentCode
    2774140
  • Title

    Pattern Mining over Star Schemas in the Onto4AR Framework

  • Author

    Antunes, Cláudia

  • Author_Institution
    Inst. Super. Tecnico, Tech. Univ. of Lisbon, Lisbon, Portugal
  • fYear
    2009
  • fDate
    6-6 Dec. 2009
  • Firstpage
    453
  • Lastpage
    458
  • Abstract
    Storing data according to the multidimensional model, in particular following star schemas, has demonstrated to be one of the most adequate forms to ease the exploration of data. However, this exploration has been limited to be query-based, leaving the discovery of hidden information to a second plan. The main reason for this, relates to the inability of traditional mining techniques to deal with several data tables at the same time. In this paper, we propose a new approach to mine patterns among data stored as a star schema, based in a domain driven framework, where available knowledge is represented in a domain ontology. Pattern mining is performed by an Apriori-based algorithm-the D2Apriori, but more efficient algorithms are being implemented and tested, in order to solve performance issues related with the large amount of data stored in data warehouses.
  • Keywords
    data mining; data warehouses; ontologies (artificial intelligence); D2Apriori; Onto4AR framework; data storage; data tables; data warehouses; domain ontology; pattern mining; star schemas; Association rules; Conferences; Data analysis; Data mining; Data warehouses; Multidimensional systems; Ontologies; Performance evaluation; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops, 2009. ICDMW '09. IEEE International Conference on
  • Conference_Location
    Miami, FL
  • Print_ISBN
    978-1-4244-5384-9
  • Electronic_ISBN
    978-0-7695-3902-7
  • Type

    conf

  • DOI
    10.1109/ICDMW.2009.68
  • Filename
    5360447