Abstract
Data mining is a process involving the application of human skill as well as technology, and as such it can be supported by clearly defined processes and procedures. This chapter presents the CRISP-DM process, one well developed standard data mining process, which contains clearly defined phases with clearly defined steps and deliverables. The nature of some of the CRISP-DM phases is such that it is possible to perform them in an e-collaboration setting. The principles for extending the CRISP-DM process to support collaborative data mining are described in the RAMSYS approach to data mining. The tools, systems, and evaluation procedures that are required for the RAMSYS approach to reach its potential are described.
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References
Adriaans, P. and Zantinge, D. (1996). Data Mining, Addison-Wesley.
Berry, M. J. A. and Linoff, G. S. (1997). Data Mining Techniques: For Marketing, Sales, and Customer Support, John Wiley & Sons.
Berthold, M. and Hand, D. J. (eds.), (1999). Intelligent Data Analysis: An introduction, Springer Verlag.
Blocked, H. and Moyle, S. A. (2002). Collaborative data mining needs centralised model evaluation. Proc. ICML’02 workshop on Data Mining: Lessons Learned,. (ed. Fawcett, T.), Sydney,spi 21–28.
Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C. and Wirth, R. (2000). CRISP-DM 1.0: Step-by-step data mining guide, CRISP-DM consortium, http://www.crisp-dm.org
Fayyad, U. M., Piatetsky-Shapiro, G. and Smyth, P. (1996). From Data Mining to Knowledge Discovery: An Overview, In (eds. Fayyad, U. M, Piatetsky-Shapiro, G., Smyth, P. and Uthurusamy, R.), Advances in Knowledge Discovery and Data Mining, AAAI Press/MIT Press.
Hand, D. J., Mannila, H. and Smyth, P. (2001). Principles of Data Mining, MIT Press.
Jorge, A., Moyle, S. and Voß, A. (2002). Remote Collaborative Data Mining Through Online Knowledge Sharing. Proc. PRO-VE’02 — 3rd IFIP Working Conference on Infrastructures for Virtual Enterprises. Sesimbra, Portugal, Kluwer Academic Press.
Kaletas, E. C., Afsarmanesh, H. and Hertzberger, L. O., (2002). Virtual Laboratories and Virtual Organizations Supporting Biosciences. Proc. PRO-VE’02 — 3rd IFIP Working Conference on Infrastructures for Virtual Enterprises. Sesimbra, Portugal, Kluwer Academic Press.
Pyle, D. (1999). Data Preparation for Data Mining, Morgan Kaufmann.
Voß, A. (2002). E-discourses with Zeno. Proc. Database and Expert Systems Applications (DEXA 2002). (eds. Troja, A. M. and Wagner, R. R.), Los Alamitos, IEEE Computer Society, 301–306.
Voß, A., Richter, G., Moyle, S. A. and Jorge, A. (2001). Collaboration support for virtual data mining enterprises. Proc. 3rd International Workshop on Learning Software Organizations (LSO’01). (ed. Müller), Lecture Notes in Computer Science, Springer-Verlag, 83–95.
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Jorge, A., Moyle, S., Blockeel, H., Voß, A. (2003). Data Mining Processes and Collaboration Principles. In: Mladenić, D., Lavrač, N., Bohanec, M., Moyle, S. (eds) Data Mining and Decision Support. The Springer International Series in Engineering and Computer Science, vol 745. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0286-9_6
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DOI: https://doi.org/10.1007/978-1-4615-0286-9_6
Publisher Name: Springer, Boston, MA
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