I present a novel approach to unsupervised concept formation based on analogy discovery, and guided by the principle of minimum description length. Preliminary results include autonomous creation of conceptual structures using a special case of analogy discovery, and a demonstration of a complete but inefficient batch version of the algorithm. I describe some shortcomings of the preliminary results, mostly concerning efficiency and local optima, and discuss how to address them.
Subjects: 12. Machine Learning and Discovery; 11.2 Ontologies
Submitted: Apr 19, 2007