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Unsupervised and Semi-Supervised Multilingual Learning for Resource-Poor Languages
Unsupervised and Semi-Supervised Multilingual Learning for Resource-Poor Languages
Diplomová práce (OBHÁJENO)
Vedoucí práce: Zeman, Daniel
Datum publikování: 2012
Datum obhajoby: 07. 09. 2012
Fakulta / součást: Matematicko-fyzikální fakulta / Faculty of Mathematics and Physics
Abstrakt: Pra ce se zaměřuje na neř zenou morfologickou segmentaci, jednu ze za kladn ch u loh poč tačov eho zpracov an přirozen eho jazyka. V t eto u loze je c lem rozložit slova na morf emy. Popisuji a reim- plementuji model ...
This thesis focuses on unsupervised morphological seg- mentation, the fundamental task in NLP which aims to break words into morphemes. I describe and re-implement a model proposed in Lee et al. (2011) and evaluate it on ...
This thesis focuses on unsupervised morphological seg- mentation, the fundamental task in NLP which aims to break words into morphemes. I describe and re-implement a model proposed in Lee et al. (2011) and evaluate it on ...