Liu, Z, Yang, L and Atwell, E orcid.org/0000-0001-9395-3764 (2019) The Semantic Annotation of the Quran Corpus Based on Hierarchical Network of Concepts Theory. In: 2018 International Conference on Asian Language Processing (IALP). IALP 2018, 15-17 Nov 2018, Bandung, Indonesia. IEEE , pp. 318-321. ISBN 978-1-7281-1175-9
Abstract
This Quran as the central religious text of Islam is widely regarded as the finest work in classical Arabic literature and plays an important role in Islam world. This paper studied and analyzed the Quran Chinese and English data, built the Quran Chinese and English words semantic knowledge base in which the grammar and semantic information of the Quranic words were described based on HNC theory, built the Quran semantic annotation corpus in which the part of speech and semantic description were annotated. The corpus with semantic annotation can help us identify the same meaning with different word forms. This paper proposed a new method of semantic analysis to solve the semantic similarity problem of natural language processing, which will benefit both the research on the semantic analysis in Natural Language Processing and the development of the Islamic Cultures.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2018, IEEE. This is an author produced version of a paper published in the proceedings of the 2018 International Conference on Asian Language Processing (IALP). Uploaded in accordance with the publisher's self-archiving policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Quran; semantic annotated corpus; semantic knowledge base; Semantics , Knowledge based systems , Grammar , Syntactics , Natural language processing , Engines , Linguistics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Apr 2019 09:20 |
Last Modified: | 05 Apr 2019 09:20 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/IALP.2018.8629241 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144495 |