Machine Learing of Morphological Rules by Generalization and Analogy

This paper describes an experimental procedure for the inductive automated learning of morphological rules from examples. At first an outline of the problem is given. Then a formalism for the representation of morphological rules is defined. This formalism is used by the automated procedure, whose anatomy is subsequently presented. Finally the performance of the system is evaluated and the most important unsolved problems are discussed.