By the same authors

Probabilistic Hierarchical Clustering Of Morphological Paradigms

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

Author(s)

Department/unit(s)

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
Pages654-663
Number of pages10
PublisherAssociation for Computational Linguistics
Place of PublicationStroudsburg, PA
Original languageEnglish
ISBN (Print)978-1-937284-19-0

Abstract

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.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations