Fast Access to Concepts in Concept Lattices via Bidirectional Associative Memories

Authors:
Rohana Rajapakse;Michael Denham
Affiliations:
School of Computing, Communications and Electronics, University of Plymouth, Plymouth, PL4 8AA, U.K.;Centre for Theoretical and Computational Neuroscience, University of Plymouth, Plymouth, PL4 8AA, U.K.
Venue:
Neural Computation
Year:
2005

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Abstract

Bidirectional associative memories (BAMs) are shown to be capable of precisely learning concept lattice structures by Radim Bělohlávek. The focus of this letter is to show that the BAM, when set up with a concept lattice by setting up connection weights according to the rule proposed by Bělohlávek, always returns the most specific or most generic concept containing the given set of objects or attributes when a set of objects or attributes is presented as input to the object or attribute layer. A proof of this property is given here, together with an example, and a brief application of the property is provided.