6533b857fe1ef96bd12b46f5
RESEARCH PRODUCT
Knowledge management challenges in knowledge discovery systems
Alexey TsymbalMykola PechenizkiySeppo Puuronensubject
Knowledge managementCommonsense knowledgebusiness.industryComputer scienceData managementKnowledge engineeringOpen Knowledge Base ConnectivityMathematical knowledge managementData scienceKnowledge-based systemsKnowledge extractionKnowledge basePersonal knowledge managementSoftware miningDomain knowledgebusinessdescription
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 data-driven 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
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2006-10-11 |