Concurrently, LEAR (re-)arranges vector norms so that norm values in the Euclidean space reflect the hierarchical organisation of concepts according to the given LE constraints: put simply, higher-level concepts are assigned larger norms.
lEAR simultaneously captures the hierarchy of concepts (through vector norms) and their similarity (through their cosine distance).