Hybrid Part-Of-Speech Tagger for Non-Vocalized Arabic Text
نویسندگان
چکیده
منابع مشابه
Part of Speech Tagger for Assamese Text
Assamese is a morphologically rich, agglutinative and relatively free word order Indic language. Although spoken by nearly 30 million people, very little computational linguistic work has been done for this language. In this paper, we present our work on part of speech (POS) tagging for Assamese using the well-known Hidden Markov Model. Since no well-defined suitable tagset was available, we de...
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Problem statement: This study presented the development of an Arabic part-of-speech tagger that can be used for analyzing and annotating traditional Arabic texts, especially the Quran text. Approach: It is a part of a project related to the computerization of the Holy Quran. One of the main objectives in this project was to build a textual corpus of the Holy Quran. Results: Since an appropriate...
متن کاملFine-Grain Morphological Analyzer and Part-of-Speech Tagger for Arabic Text
Morphological analyzers and part-of-speech taggers are key technologies for most text analysis applications. Our aim is to develop a part-of-speech tagger for annotating a wide range of Arabic text formats, domains and genres including both vowelized and non-vowelized text. Enriching the text with linguistic analysis will maximize the potential for corpus re-use in a wide range of applications....
متن کاملProbabilistic Arabic Part of Speech Tagger with Unknown Words Handling
Part Of Speech (POS) tagger is an essential preprocessing step in many natural language applications. In this paper, we investigate the best configuration of trigram Hidden Markov Model (HMM) Arabic POS tagger when small tagged corpus is available. With small training data, unknown word POS guessing is the main problem. This problem becomes more serious in languages which have huge size of voca...
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ژورنال
عنوان ژورنال: International Journal on Natural Language Computing
سال: 2013
ISSN: 2319-4111,2278-1307
DOI: 10.5121/ijnlc.2013.2601