By the same authors

Probabilistic Hierarchical Clustering Of Morphological Paradigms

Research output: Chapter in Book/Report/Conference proceedingConference contribution



Publication details

Title of host publicationEACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
DatePublished - 23 Apr 2012
Number of pages10
PublisherAssociation for Computational Linguistics
Place of PublicationStroudsburg, PA
Original languageEnglish
ISBN (Print)978-1-937284-19-0


We propose a novel method for learning morphological paradigms that are structured within a hierarchy. The hierarchical structuring of paradigms groups morphologically similar words close to each other in a tree structure. This allows detecting morphological similarities easily leading to improved morphological segmentation. Our evaluation using (Kurimo et al., 2011a; Kurimo et al., 2011b) dataset shows that our method performs competitively when compared with current state-of- art systems.

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