How to increase both autonomy and versatility of a knowledge discovery system is a core problem and a crucial aspect of KDD (Knowledge Discovery and Data Mining). We have been developing a multi-agent based KDD methodology/system called GLS (Global Learning Scheme) for performing multi-aspect intelligent data analysis as well as multi-level conceptual abstraction and learning. With multi-level and multi-phase process, GLS increases versatility and autonomy. This paper presents our recent development on the GLS methodology/system.
CITATION STYLE
Zhong, N., Matsui, Y., Okuno, T., & Liu, C. (2001). Framework of a multi-agent KDD system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2412, pp. 337–346). Springer Verlag. https://doi.org/10.1007/3-540-45675-9_51
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