Abstract
This article proposes a system based on the interpretation on the Quranic text that has been translated into English language using word sense disambiguation. This system is based on a combination of three traditional semantic similarity measurements, which are Wu-Palmer (WUP), Lin (LIN), and Jiang-Conrath (JCN) for word sense disambiguation on the English Al-Quran. The experiment was performed to obtain the best overall similarity score. The empirical results demonstrate that the combination of the three mentioned semantic similarity techniques obtained competitive results when compared with using individual similarity measurements.
Highlights
The Holy Quran is the central religious verbal text of Islam, and the right understanding of the Quranic text is very necessary for Muslim people
Research Method There are three traditional semantic relatedness sequential approaches applied in computational linguistics, which can be used to measure and resolve problems associated with word sense disambiguation
Evaluation and Experimental Results The purpose of word sense disambiguation in the context of this study is based on target words that appear in data prepared from the Quranic texts
Summary
The Holy Quran is the central religious verbal text of Islam, and the right understanding of the Quranic text is very necessary for Muslim people. It is the religious text of more than 1.5 billion Muslims around the world, who speak in different languages. It was consists of 114 ‘surah’ (chapters), which have obvious textual boundaries. The longer ‘surah’ appear earlier in the Quran, while the shorter ones appear later. The Arabic Quranic corpus consists of 77,784 word tokens and 19,287 word types [14, 15, 16]
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