Abstract
We have been developing a methodology and system for autonomous knowledge discovery and data mining from global information sources. The key issue is how to increase both autonomy and versatility of our discovery system. Our methodology is to create an organized society of autonomous knowledge discovery agents. This means (1) to develop many kinds of knowledge discovery and data mining agents (KDD agents in short) for different objects; (2) to use the KDD agents in multiple learning phases in a distributed cooperative mode; (3) to manage the society of the KDD agents by multiple meta-control levels. Based on this methodology, a multi-strategy and cooperative discovery system, which can be imagined as a softbot and is named GLS (Global Learning Scheme), has being developing by us. This paper briefly describes our methodology and the framework of our GLS system.
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Zhong, N., Kakemoto, Y., Ohsuga, S. (1997). An organized society of autonomous knowledge discovery agents. In: Kandzia, P., Klusch, M. (eds) Cooperative Information Agents. CIA 1997. Lecture Notes in Computer Science, vol 1202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62591-7_33
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DOI: https://doi.org/10.1007/3-540-62591-7_33
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