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Suresh Manandhar
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Journal Articles
Publisher: Journals Gateway
Computational Linguistics (2018) 44 (2): 349–374.
Published: 01 June 2018
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This article presents a probabilistic hierarchical clustering model for morphological segmentation. In contrast to existing approaches to morphology learning, our method allows learning hierarchical organization of word morphology as a collection of tree structured paradigms. The model is fully unsupervised and based on the hierarchical Dirichlet process. Tree hierarchies are learned along with the corresponding morphological paradigms simultaneously. Our model is evaluated on Morpho Challenge and shows competitive performance when compared to state-of-the-art unsupervised morphological segmentation systems. Although we apply this model for morphological segmentation, the model itself can also be used for hierarchical clustering of other types of data.
Journal Articles
Publisher: Journals Gateway
Computational Linguistics (2002) 28 (2): 224–228.
Published: 01 June 2002