Paper: Probabilistic Hierarchical Clustering of Morphological Paradigms

ACL ID E12-1067
Title Probabilistic Hierarchical Clustering of Morphological Paradigms
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2012
Authors

We propose a novel method for learning morphological paradigms that are struc- tured within a hierarchy. The hierarchi- cal structuring of paradigms groups mor- phologically similar words close to each other in a tree structure. This allows detect- ing morphological similarities easily lead- ing to improved morphological segmen- tation. Our evaluation using (Kurimo et al., 2011a; Kurimo et al., 2011b) dataset shows that our method performs competi- tively when compared with current state-of- art systems.