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A Systemic Framework for the Field of Data Mining and Knowledge Discovery

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4 Author(s)
Yi Peng ; Coll. of Inf. Sci. & Technol., Nebraska Univ., Omaha, NE ; Gang Kou ; Yong Shi ; Zhengxin Chen

This paper proposes a systemic framework that attempts to define the domain and major areas of data mining and knowledge discovery (DMKD). Grounded theory approach, a qualitative method that inductively develops an understanding of phenomena, is adopted to build the framework. Using a large collection of DMKD literature, including DMKD journals, conference proceedings, syllabuses, and dissertations, this study develops a framework of eight main areas for the field: (1) foundations of DMKD; (2) learning methods & techniques; (3) mining complex data; (4) high-performance & distributed data mining; (5) data mining software & systems; (6) data mining process & project; (7) data mining applications; (8) data mining tasks. The last area is suggested as the central theme of the field

Published in:

Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on

Date of Conference:

Dec. 2006

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