| Issue |
MATEC Web Conf.
Volume 135, 2017
8th International Conference on Mechanical and Manufacturing Engineering 2017 (ICME’17)
|
|
|---|---|---|
| Article Number | 00070 | |
| Number of page(s) | 9 | |
| DOI | https://doi.org/10.1051/matecconf/201713500070 | |
| Published online | 20 November 2017 | |
An Ontological Approach towards Dialoguebased Information Visualization System: Quran Corpus for Juz' Amma
1
Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.
2
Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
* Corresponding author: aminy@uthm.edu.my
This paper presents a corpus that offers rich and authentic knowledge for Juz' Amma using the ontological engineering approach. The reason of the study conducted is because of lack of understanding of Juz' Amma in the form of listing result. At the same time, the listing result does not provide pictorial tidings for clustering the listing result. Therefore, the corpus covers knowledge from various authentic sources, including translation, annotation of keywords, tafsir, and related hadiths for every verse in English and Malay. The ontology is engineered and designed to effectively utilize the authentic knowledge extracted from the corpus intended to serve a dialogue-based information visualization system for Quranic text. A standard ontology engineering methodology was applied for developing the ontology. After creation, the ontology was evaluated and was found to fulfill the goals for which it was developed. The corpus and ontology are hoped to aid various semantic applications related to Quranic text in the future.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.