Reproductive Process-Oriented Data Mining from Interactions between Human and Complex Artifact System

Authors:
Tetsuo Sawaragi
Affiliations:
-
Venue:
MLDM '99 Proceedings of the First International Workshop on Machine Learning and Data Mining in Pattern Recognition
Year:
1999

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Abstract

This paper presents a method for concept formation of a personal learning apprentice (PLA) system that attempts to capture users' internal conceptual structure by observing interactions between user and system. Current hot topics on techniques of data mining may potentially contribute to the above purpose, but different from the conventional approaches of data mining, we have to consider more about the aspects in which how the mined knowledge should be used by the human in the consequent processes, not only about what knowledge should be extracted. In this paper we propose such a process-oriented data mining method based upon an idea of soft systems methodologies proposed by P.B. Checkland in 1980's, and we propose an algorithm for its implementation using evolutional computing.