Discovering Qur'anic Knowledge through AQD: Arabic Qur'anic Database, a Multiple Resources Annotation-level Search

被引：0

作者：

Alrehaili, Sameer M. ^{[1
]}

Atwell, Eric ^{[2
]}

机构：

[1] Taibah Univ, Coll Sci & Comp Engn, Yanbu, Saudi Arabia

[2] Univ Leeds, Sch Comp, Leeds, W Yorkshire, England

来源：

2018 IEEE 2ND INTERNATIONAL WORKSHOP ON ARABIC AND DERIVED SCRIPT ANALYSIS AND RECOGNITION (ASAR) | 2018年

关键词：

extraction; Quran; query language;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces a novel resource for Arabic Qur'anic textual annotations: AQD, Arabic Qur'anic Database, providing an annotation-level search that draws on a number of available resources in a single query. In addition, it allows implementing a set of queries as rewrite rules, which is performed in a recursive way. The experiments show that our AQD is able to discover knowledge from very simple to very complex queries.

引用

页码：102 / 107

页数：6

共 2 条

[1] A Hybrid Methods of Aligning Arabic Qur'anic Semantic Resources
Alrehaili, Sameer M.
Alqahtani, Mohammad
Atwell, Eric
2018 IEEE 2ND INTERNATIONAL WORKSHOP ON ARABIC AND DERIVED SCRIPT ANALYSIS AND RECOGNITION (ASAR), 2018, : 108 - 113
[2] Learning Qur'anic Arabic through Interactive Web-Based Software: A Pragmatic Approach in Language for Specific Purpose
Abdullah, Matin Saad
Pathan, Al-Sakib Khan
2013 5TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY FOR THE MUSLIM WORLD (ICT4M), 2013,

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