Knowledge Management Challenges in Knowledge Discovery Systems

Current knowledge discovery systems are armed with many data mining techniques that can be potentially applied to a new problem. However, a system faces a challenge of selecting the most appropriate technique(s) for a problem at hand, since in the real domain area it is infeasible to perform a comparison of all applicable techniques. The main goal of this paper is to consider the limitations of datadriven approaches and propose a knowledge-driven approach to enhance the use of multiple data-mining strategies in a knowledge discovery system. We introduce the concept of (meta-) knowledge management, which is aimed to organize a systematic process of (meta-) knowledge capture and refinement over time.

• Type: Conference
• Year: 2005
• Where: DEXAW
• Authors: Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
• Keywords: Current Knowledge Discovery, Data Mining Techniques, Database, DEXAW 2005, Knowledge Discovery System