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This paper presents several industrial applications of ML in the context of their effort to solve the "KAML problem", i.e., the problem of merging knowledge acquisition and machine learning techniques. Case-based reasoning is a possible alternative to the problem of acquiring highly compiled expert knowledge, but it raises also many new problems that must be solved before really efficient implementations are available.

Industrial applications of ML: Illustrations for the KAML dilemma and the CBR dream