%0 Journal Article
%T Unsupervised learning of morphological families: comparison of methods and multilingual aspects Apprentissage non supervise  de familles morphologiques : comparaison de me thodes et aspects multilingues
%A Delphine Bernhard
%J Traitement Automatique des Langues
%D 2011
%I Association pour le Traitement Automatique des Langues (ATALA)
%X This article describes MorphoClust and MorphoNet, two methods for the unsupervised acquisition of morphological families. MorphoClust builds families by iterative conflations, similarly to hierchical clustering methods. The MorphoNet method relies on community detection in lexical networks. The nodes of these networks stand for words while edges represent morphological transformation rules which are automatically acquired based on graphical similarities between words. The two methods are applied to a German-English bilingual lexicon, both in isolation and in combination. We evaluate the results using the CELEX lexical database.
%K morphology
%K unsupervised learning
%K system combination
%U http://www.atala.org/IMG/pdf/2-Bernhard-TAL51-2.pdf