• DocumentCode
    2869045
  • Title

    Organization-Ontology Based Framework for Implementing the Business Understanding Phase of Data Mining Projects

  • Author

    Sharma, Sumana ; Osei-Bryson, Kweku-Muata

  • Author_Institution
    Virginia Commonwealth Univ., Richmond
  • fYear
    2008
  • fDate
    7-10 Jan. 2008
  • Firstpage
    77
  • Lastpage
    77
  • Abstract
    CRISP-DM is a detailed and widely used data mining methodology that aims to provide explicit guidance regarding how the various phases of a data mining project could be executed. The ´business understanding´ phase marks the beginning of a data mining project and forms the foundation for the execution of the remaining phases. Unfortunately, the real-world implementation of this pivotal phase is performed in a rather unstructured and ad-hoc manner. We argue that the reason for this lies in the lack of support in form of appropriate tools and techniques that can be used to execute the large number of activities (=67) prescribed within this phase. This paper presents an organization-ontology based framework that not only incorporates the applicable tools and techniques, but also provides the ability to present the output of activities in a form that allows for at least their semi-automated integration with activities of this phase and succeeding phases.
  • Keywords
    data mining; ontologies (artificial intelligence); cross industry standard process for data mining; data mining projects; organization-ontology based framework; semi-automated integration; Costs; Data mining; Databases; Decision making; Delta modulation; Information systems; Mining industry; Navigation; Phased arrays; Surges;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hawaii International Conference on System Sciences, Proceedings of the 41st Annual
  • Conference_Location
    Waikoloa, HI
  • ISSN
    1530-1605
  • Type

    conf

  • DOI
    10.1109/HICSS.2008.339
  • Filename
    4438780