Morphological segmentation using Dirichlet process based bayesian non-parametric models

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Enformatik Enstitüsü, Bilişsel Bilimler Anabilim Dalı, Türkiye

Tezin Onay Tarihi: 2016

Öğrenci: SERKAN KUMYOL

Danışman: HÜSEYİN CEM BOZŞAHİN

Özet:

This study, will try to explore models explaining distributional properties of morphology within the morphological segmentation task. There are di erent learning approaches to the morphological segmentation task based on supervised, semi-supervised and unsupervised learning. The existing systems and how well semi-supervised and unsupervised non-parametric Bayesian models t to the segmentation task will be investigated. Furthermore, the role of occurrence independent and co-occurrence based models in morpheme segmentation will be investigated.