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A Rich Arabic WordNet Resource for Al-Hadith Al-Shareef
Author(s) -
Manar Alkhatib,
Azza Abdel Monem,
Khaled Shaalan
Publication year - 2017
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2017.10.098
Subject(s) - wordnet , computer science , natural language processing , artificial intelligence , arabic , linguistics , machine translation , philosophy
Most Arabic computational linguistics researchers have focused on Modern Standard Arabic. Linguistic resources and tools for Classical Arabic, especially Al-Hadith Al-Shareef (i.e. the Prophet Muhammad’s saying), remain relatively unexplored, despite its importance as a reference, in addition to its use in the holy Qur’an, used by all Muslims worldwide. Computational linguistics research tools for Al-Hadith Al-Shareef would be useful for both Islamic scholars and learners. Arabic WordNet is a remarkable language resource on its own, allowing a user to determine the relationships among words. It has proven its importance in many of language processing tasks needing an understanding of the meaning of language, including Information Retrieval, Word Sense Disambiguation, Machine Translation, Question Answering, Text Classification, and Text Summarization. In this paper, we propose an approach for developing a WordNet linguistic resource for Al-Hadith Al-Shareef that serves its purposes for various Arabic natural language processing tasks. In particular, we establish semantic connections between words in order to achieve a good understanding of the meanings of the Al-Hadith words. Our approach employs Classical Arabic dictionaries and Al-Hadith ontology. Al-Hadith WordNet has demonstrated its capability in a text classification task that we developed for evaluation proposes. The classifier has been applied on around 8500 synsets that include 6126 nominal, 1990 verbal, 310 adjectival, and 71 adverbial expressions.

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