Similarity Evaluation of English Translations of the Holy Quran

In this paper, similarity evaluation of English translations of the Holy Quran using four computational methods is performed. The computational methods are bag of words, term-frequency, tfidf and latent semantic indexing. We used twenty-one translation pairs from seven English translations (Hilali, Yusuf Ali, Sahih, Shakir, Arberry, Pickthall, Maududi) in our experiments. The similarity measures were evaluated pair wise. Based on our results, seven translations pair have high similarity measures, (Hilali, Yusuf Ali), (Hilali, Sahih), (Sahih, Shakir), (Hilali, Pickthall), (Pickthall, Shakir), (Hilali, Shakir), (Shakir, Arberry). We have nine translation pairs with low similarity measures, (Hilali, Maududi), (Maududi, Pick-thall), (Maududi, Yusuf Ali), (Hilali, Arberry), (Arberry, Yusuf Ali), (Maududi, Arberry), (Pickthall, Yusuf Ali), (Shahih, Yusuf Ali), (Pickthall, Sahih). These results from a computational perspective offer new insights into the similarity evaluation between the English translations based on computation methods. Also, we concluded the translations of (Hilali, Sahih, Shakir, Yusuf Ali, Pickthall) could be clustered into one group, and the translations of (Maududi, Arberry) into another group. These results could be used for classification of English translations and for comparing future translations.