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Comparison of ontology learning techniques for Qur'anic text

Yong, C.Y. and Sudirman, Rubita and Chew, K. M. and Salim, Naomie (2011) Comparison of ontology learning techniques for Qur'anic text. In: Proceedings - 2011 International Conference on Future Computer Sciences and Application, ICFCSA 2011. IEEE Explorer, pp. 192-196. ISBN 978-076954422-9

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Official URL: http://dx.doi.org/10.1109/ICFCSA.2011.50

Abstract

Currently, ontology plays an important role in semantic web technology. Ontology learning approach is to distinguish the type of input such as text, dictionary, knowledge, policies, schemes and semi-structured schemes relations. Ontology learning can be explained as information extraction subtask and its objectives are to dig the relevant concepts and relationships from the corpus or a particular type of data sets. In this project, an ontology learning of text extraction from Qur'anic text as input data was assessed using a newly developed support system. The algorithms used to extract Qur'anic text in this project are Alfonseca & Manandhar's and Gupta & Colleagues's approach. The support system will assess and evaluate these two algorithms and compare with the manually text extraction (Gold Standard) in order to come out an appropriate method or technique which suitable to extract the ontologies from Qur'anic text which can help more people to understand the true meaning from Qur'an teaching.

Item Type:Book Section
Uncontrolled Keywords:classification, natural language, ontology learning, recognition, text extraction
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:28930
Deposited By: Liza Porijo
Deposited On:04 Dec 2012 06:25
Last Modified:04 Dec 2012 06:25

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