Characterising data mining software

Intelligent Data Analysis

Volumn 7, Issue 3, 2003, Pages 181-192

  Giraud Carrier, C ^a   Povel, O ^a  

^a ELCA Informatique SA   (Switzerland)

Author keywords

business decision support; data mining; tool characterisation; tool comparison

Indexed keywords

DECISION SUPPORT SYSTEMS;

BUSINESS DECISION SUPPORTS; BUSINESS REQUIREMENT; COMMERCIAL SOFTWARE; DATA MINING APPLICATIONS; DATA-MINING SOFTWARE; DATA-MINING TOOLS; STANDARD BASIS; TOOL COMPARISONS;

DATA MINING;

EID: 22144492593     PISSN: 1088467X     EISSN: 15714128     Source Type: Journal    
DOI: 10.3233/ida-2003-7302     Document Type: Article

References (21)

1. F. Bihan, Comparison of Leading Data Mining Tools, Available at http://www.ksurf.net/cs761/.
2. R.J. Brachman and T. Anand, The Process of Knowledge Discovery in Databases: A Human-centered Approach, in: Advances in Knowledge Discovery and Data Mining, U.M. Fayyad, G. Piatetsky-Shapiro and P. Smyth, eds, AAAI/MIT Press, 1996, pp. 33-51.
3. K. Collier, B. Carey, D. Sautter and C. Marjaniemi, A Methodology for Evaluating and Selecting Data Mining Software, in Proceedings of the Thirty Second Hawaii International Conference on System Sciences, Available at http://www.cse.nau.edu, 1999.
4. CRISP-DM 1.0: Step-by-step data mining guide, Available as an SPSS White Paper at http://www.spss.com.
5. Criteria for Data Mining Tool Evaluation, Available at http://www.catenate.net/a basic checklist for a high per.htm.
6. Data Mining, Available at http://www.dwinfocenter.org/datamine.html.
7. Data Mining Catalogue, Available at http://datamining.csiro.au/catalogue. html.
8. Data Mining Product Features, Available at http://www.xore.com/prodtable. html.
9. J.F. Elder and D.M. Abbott, A Comparison of Leading Data Mining Tools, in Proceedings of the Fourth Annual Conference on Knowledge Discovery and Data Mining (KDD'98), Available at http://www.datamininglab.com, 1998.
10. U. Fayyad, G. Piatetsky-Shapiro and P. Smyth, The KDD Process for Extracting Useful Knowledge from Volumes of Data, Communications of the ACM 39(11) (1996), 27-34.
11. L. Fontaine, Industrial KDD Systems, Available at http://www.lri.fr/blf/ results, 1999.
12. From Data to Business Advantage: Data Mining, The SEMMA Methodology and SAS Software, Available as a SAS Institute White Paper at http://www.sas.com.
13. W. Gaul and F. Saeuberlich, Classification and Positioning of Data Mining Tools, in: Classification in the Information Age, W. Gaul and H. Locarek-Junge, eds, Springer, Berlin, Heidelberg, 1999, pp. 143-152.
14. KDnuggets Poll: Data mining tools you regularly use, Available at http://www.kdnuggets.com/polls/data mining tools 2002 june2.htm.
15. KDnuggets Poll: What main methodology are you using for data mining? Available at http://www.kdnuggets.com/polls/methodology.htm.
16. M.A. King and J.F. Elder, Evaluation of Fourteen Desktop Data Mining Tools, in Proceedings of the 1998 IEEE International Conference on Systems, Man and Cybernetics, 1998, Available at http://www.datamininglab.com.
17. List of Software, Available at http://www.mlnet.org.
18. H. Mannila, Methods and Problems in Data Mining, in Proceedings of the 1997 International Conference on Database Theory, 1997.
19. M. Mendonca and N.L. Sunderhaft, Mining Software Engineering Data: A Survey, Data & Analysis Center for Software (DACS) State-of-the-Art Report, No. DACS-SOAR-99-3, 1999, Available at http://www.dacs.dtic.mil/techs/datamin ing/index.html.
20. METAL: A Meta-learning Assistant for Providing User Support in Machine Learning and Data Mining, European ESPRIT Project Nr 26.357, See http://www.metal-kdd.org.
21. K. Parsaye, A Characterization of Data Mining Technologies and Processes, Journal of Data Warehousing, December 1997, Available at http://www.datamining. com/dm-tech.htm.