Lessons Learned From Data Mining, Decision Support and Collaboration
This chapter reports on the experience of the partners of the SolEuNet project in solving data mining and decision support problems in a collaborative way. The lessons learned are presented from the following perspectives: research, business, collaborative problem solving, and customer applications of data mining, text mining and decision support methods.
KeywordsMarketing Assure Expense Editing
Unable to display preview. Download preview PDF.
- Bohanec, M. and Zupan, B. (2001). Integrating decision support and data mining by hierarchical multi-attribute decision models. Proc. ECML/PKDD-2001 Workshop Integrating Aspects of Data Mining, Decision Support and Meta-Learning (IDDM-2001). (eds. Giraud-Carrier, C., Lavrač, N., Moyle, S. A. and Kavšek, B.), Freiburg, Germany, 25–36.Google Scholar
- Grobelnik, M. and Mladenić, D. (2002a). Approaching Analysis of EU 1ST Projects Database. Proc. IIS 2002, 13th International Conference on Information and Intelligent Systems. (eds. Aurer, B. and Lovrencic, A.), Varaždin, Croatia, Faculty of Organization and Informatics; Zagreb, University of Zagreb, 57–61.Google Scholar
- Grobelnik, M. and Mladenić, D. (2002b). Efficient visualization of large text corpora. Proc. 7th TELRI seminar. Dubrovnik, Croatia.Google Scholar
- Grobelnik, M., Mladenić, D. and Jermol, M. (2002). Exploiting text mining in publishing and education. Proc. Information Society IS-2002. (eds. Grobelnik, M., Bohanec, M., Mladenić, D. and Gams, M.), Ljubljana, Slovenia, Jožef Stefan Institute.Google Scholar
- Steinbach, M., Karypis, G. and Kumar, V. (2000). A comparison of document clustering techniques. Proc. KDD Workshop on Text Mining, (eds. Grobelnik, M., Mladenić, D. and Milic-Frayling, N.), Boston, MA, USA, 109–110.Google Scholar