Automatic Learning for Supporting Advanced Human-Machine Interfaces

This paper provides a novel algorithm for supporting automatic learning oriented to advanced human-machine interfaces. The algorithm introduces several points of innovativeness, based on complex similarity metrics involving several features of the whole learning process. A comprehensive experimental assessment and analysis of the proposed algorithm on both synthetic and real-life data sets confirms the benefits deriving from our proposal.

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