خط مشی دسترسیدرباره ماپشتیبانی آنلاین
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Document Type:Latin Dissertation
Language of Document:English
Record Number:53096
Doc. No:TL23050
Call number:‭1459900‬
Main Entry:Azadeh Monirabbassi
Title & Author:Part of Speech tagging of LevantineAzadeh Monirabbassi
College:University of California, San Diego
Date:2008
Degree:M.S.
student score:2008
Page No:50
Abstract:The goal for this project is to explore strategies in adapting a Part of Speech (POS) tagger that was trained on Modern Standard Arabic sentences for tagging Levantine sentences, a dialect of Modern Standard Arabic, leveraged by methods of morphological analysis. I propose a tagging model that supports an explicit representation of the root-template patterns of Arabic. I will analyze the functionality and performance of the algorithms, and will compare the results. In leveraging the MSA POS tagger for tagging Levantine data, I achieved a peak accuracy of 73.28% which is 6% higher than the baseline for a standard Hidden Markov Model based tagger.
Subject:Applied sciences; Arabic; Computational linguistics; Linguistics; Machine learning; Natural language processing; Artificial intelligence; Computer science; 0984:Computer science; 0800:Artificial intelligence
Added Entry:G. W. L. Cottrell, Roger
Added Entry:University of California, San Diego