Towards Flexibility in a Distributed Data Mining Framework José Maria Peña and Ernestina Menasalvas   View Paper (PDF)   Return to Position Papers Abstract Commercial data mining systems are becoming more and more complex. Advances features like, extensible algorithm toolboxes and programming APIs, allow these systems to include new operations to mine and to prepare data. Although these characteristics are necessary trends performance can not be compromised. In order to keep the balance between functionality and performance new design strategies are needed. In this paper we present a fexible control architecture for distributed data mining. DiSC'02 © 2003 Association for Computing Machinery