New Instances Classification Framework On Quran Ontology Applied To Question Answering System

Utomo, Fandy Setyo and Suryana, Nanna and Azmi, Mohd Sanusi (2019) New Instances Classification Framework On Quran Ontology Applied To Question Answering System. Telkomnika (Telecommunication Computing Electronics and Control), 17 (1). 139 - 146. ISSN 1693-6930

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Abstract

Instances classification with the small dataset for Quran ontology is the current research problem which appears in Quran ontology development. The existing classification approach used machine learning: Backpropagation Neural Network. However, this method has a drawback; if the training set amount is small, then the classifier accuracy could decline. Unfortunately, Holy Quran has a small corpus. Based on this problem, our study aims to formulate new instances classification framework for small training corpus applied to semantic question answering system. As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. This algorithm is chosen since it robustness to noisy data and has an excellent achievement to handle small dataset. Furthermore, document processing module on question answering system is used to access instances classification result in Quran ontology.

Item Type:	Article
Uncontrolled Keywords:	Information retrieval, Ontology, Ontology learning, Ontology population, Question answering system, Quran Ontology
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Sabariah Ismail
Date Deposited:	28 Oct 2020 11:17
Last Modified:	28 Oct 2020 11:17
URI:	http://eprints.utem.edu.my/id/eprint/24354
Statistic Details:	View Download Statistic

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