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Vol 17, No 1: February 2019

New instances classification framework on Quran ontology applied to question answering system

Fandy Setyo Utomo (STMIK AMIKOM Purwokerto)
Nanna Suryana (Universiti Teknikal Malaysia Melaka)
Mohd Sanusi Azmi (Universiti Teknikal Malaysia Melaka)

Article Info

Publish Date
01 Feb 2019


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.

Copyrights © 2019

Journal Info





Computer Science & IT


Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...