Organization-Ontology Based Framework for Implementing the Business Understanding Phase of Data Mining Projects
2014 47th Hawaii International Conference on System Sciences (2008)
Waikoloa, Big Island, Hawaii
Jan. 7, 2008 to Jan. 10, 2008
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.
Kweku-Muata Osei-Bryson, Sumana Sharma, "Organization-Ontology Based Framework for Implementing the Business Understanding Phase of Data Mining Projects", 2014 47th Hawaii International Conference on System Sciences, vol. 00, no. , pp. 77, 2008, doi:10.1109/HICSS.2008.339