Published: 1997 Juni
Buchtitel: Proceedings of the 1st European Symposium on Principles of Data Mining and Knowledge Discovery, Trondheim, Norway
Knowledge Discovery in Databases (KDD) is currently a hot topic in industry and academia. Unfortunately, the focus of research behind most emerging products is on underlying algorithms and modelling techniques. The main bottleneck for KDD applications is not the lack of techniques. The challenge is to exploit and combine existing algorithms effectively. In this paper, we describe the project Citrus which addresses these practically relevant issues. Starting from a commercially available system, we develop a scalable, extensible tool inherently based on the view of KDD as an interactive and iterative process. In this paper we sketch the main components of this system, namely an information manager for effective retrieval of data and results, an execution server for efficient execution, and a process support interface for guiding the user through the process.