Journal Papers
“Knowledge Discovery in Databases: An Overview” U. Fayyad, in Relational Data Mining, S. Dzeroski and N. Lavrac (eds), pp. 28-47, Berlin: Springer-Verlag, (2001)
“Data Mining: The Next 10 Years” Usama M. Fayyad, Gregory Piatesfky-Shapiro, Ramasamy Uthurusamy. ACM SIGKDD Explorations Newsletter, Vol. 5, Issue 2, pp. 191-196, December (2003).
“The digital physics of data mining” U. Fayyad, Communications of the ACM, Vol. 44, Issue 3, pp. 62-65, March (2001).
Being asked to project the future state of data mining is like being asked to predict what the descendants of a newborn baby will
“Cataloging and mining massive databases for science data analysis” U. Fayyad and P. Smyth, Journal of Computational Graphics and Statistics, Vol. 8, No. 3, pp. 589-610, September (1999).
Abstract With hardware advances in sensors, scientific instruments, and data storage techniques has come the inevitable flood of data that threatens to render traditional
“Mathematical Programming for Data Mining: Formulations and Challenges” P.S. Bradley, U.M. Fayyad, and O.L. Mangasarian,. INFORMS Journal on Computing, Vol.11, Issue 3, pp. 217-238, August (1999).
“Mining Databases: Towards Algorithms for Knowledge Discovery” Usama Fayyad.. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, Vol. 21, No. 1, pp. 39-48, March (1998).
1 Introduction Data Mining and Knowledge Discovery in Databases (KDD) are rapidly evolving areas of research that are at the intersection of several disciplines,