Arabic Computational Morphology: Knowledge-based and Empirical Methods

Author:   Abdelhadi Soudi ,  Antal van den Bosch ,  Günter Neumann
Publisher:   Springer
Edition:   Softcover reprint of hardcover 1st ed. 2007
Volume:   39
ISBN:  

9789048175154


Pages:   308
Publication Date:   18 November 2010
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Arabic Computational Morphology: Knowledge-based and Empirical Methods


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Overview

This is the first comprehensive overview of computational approaches to Arabic morphology. The subtitle aims to reflect that widely different computational approaches to the Arabic morphological system have been proposed. The book provides a showcase of the most advanced language technologies applied to one of the most vexing problems in linguistics. It covers knowledge-based and empirical-based approaches.

Full Product Details

Author:   Abdelhadi Soudi ,  Antal van den Bosch ,  Günter Neumann
Publisher:   Springer
Imprint:   Springer
Edition:   Softcover reprint of hardcover 1st ed. 2007
Volume:   39
Weight:   0.506kg
ISBN:  

9789048175154


ISBN 10:   9048175151
Pages:   308
Publication Date:   18 November 2010
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Arabic Computational Morphology: Knowledge-based and Empirical Methods.- On Arabic Transliteration.- Issues in Arabic Morphological Analysis.- Knowledge-Based Methods.- A Syllable-based Account of Arabic Morphology.- Inheritance-based Approach to Arabic Verbal Root-and-Pattern Morphology.- Arabic Computational Morphology: A Trade-off Between Multiple Operations and Multiple Stems.- Grammar-Lexis Relations in the Computational Morphology of Arabic.- Empirical Methods.- Learning to Identify Semitic Roots.- Automatic Processing of Modern Standard Arabic Text.- Supervised and Unsupervised Learning of Arabic Morphology.- Memory-based Morphological Analysis and Part-of-speech Tagging of Arabic.- Integration of Arabic Morphology in Larger Applications.- Light Stemming for Arabic Information Retrieval.- Adapting Morphology for Arabic Information Retrieval*.- Arabic Morphological Representations for Machine Translation.- Arabic Morphological Generation and its Impact on the Quality of Machine Translation to Arabic.

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