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Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
ISBN: 0-7695-2702-7
pp: 395-399
Yi Peng , University of Nebraska at Omaha
Gang Kou , Thomson Legal & Regulatory, R&D, 610 Opperman Drive, Eagan, MN
Yong Shi , Graduate University of the Chinese Academy of Sciences, 100080, China
Zhengxin Chen , University of Nebraska at Omaha
ABSTRACT
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) highperformance & 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. Keywords: Data mining and knowledge discovery, Grounded theory, Theoretic framework.
INDEX TERMS
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CITATION
Yi Peng, Gang Kou, Yong Shi, Zhengxin Chen, "A Systemic Framework for the Field of Data Mining and Knowledge Discovery", ICDMW, 2006, 2013 IEEE 13th International Conference on Data Mining Workshops, 2013 IEEE 13th International Conference on Data Mining Workshops 2006, pp. 395-399, doi:10.1109/ICDMW.2006.24
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