Promoting Data Mining Methodologies by Architecture-Level Optimizations

This paper presents a new theoretical data mining framework that adapts the existing data mining systems with the architecture of the Knowledge Grid, the mechanism of the ontologies, and the factor of the human-driven knowledge. Aiming at much of the research to date focusing on the technique and algorithms, the new framework describes the essential factors from systemic and technical viewpoints respectively in order to balance the effect between the two aspects.