Mini-Batch k-Means versus k-Means to Cluster English Tafseer Text: View of Al-Baqarah Chapter

Abstract

Al-Quran is the primary text of Muslims’ religion and practise. Millions of Muslims around the world use al-Quran as their reference guide, and so knowledge can be obtained from it by Muslims and Islamic scholars in general. Al-Quran has been reinterpreted to various languages in the world, for example, English and has been written by several translators. Each translator has ideas, comments and statements to translate the verses from which he has obtained (Tafseer). Therefore, this paper tries to cluster the translation of the Tafseer using text clustering. Text clustering is the text mining method that needs to be clustered in the same section of related documents. The study adapted (mini-batch k-means and k-means) algorithms of clustering techniques to explain and to define the link between keywords known as features or concepts for Al-Baqarah chapter of 286 verses. For this dataset, data preprocessing and extraction of features using Term Frequency-Inverse Document Frequency (TF-IDF) and Principal Component Analysis (PCA) applied. Results showed that two/three-dimensional clustering plotting assigning seven cluster categories (k = 7) for the Tafseer. The implementation time of the mini-batch k-means algorithm (0.05485s) outperformed the time of the k-means algorithm (0.23334s). Finally, the features ‘god’, ‘people’, and ‘believe’ was the most frequent features.

Prioritise Five Tafseer Translators Using Clustering Technique for Surah Al-Baqarah

“…According to the studies [26], [29], [30], [43], chapter Al-Baqarah can be clustered using , hence the study experments applied this value for the all five translotor (TR1-TR5). Table 3 shown k-means algorithm results of internal validation metrics (SC, DBI) and the execution time (ET) in addition to features statistics.…”

“…However, the DBSCAN algorithm got some clustering noise. [30] Surah The study proved the Mini Batch K-means cluster algorithm outperforms the standard k-means algorithm in terms of the execution time of clustering (faster) for Surah Al-Baqarah English Tafseer (where the number of clusters was seven).…”

“…The corresponding verses are then organised into seven key themes or issues (see Figure 1). Therefore, the ideal value of k for clustering the Al-Baqarah chapter for the five cluster algorithms is seven and applied for all five TR [4], [26], [28]- [30], [38]. Hence, two algorithms are used and mentioned in the introduction before as follows:-1.k-means The k-means algorithm is the fundamental form of cluster partitioning algorithms.…”

K-means variations analysis for translation of English Tafseer Al-Quran text

“…The ideal number of clusters used to cluster chapter Al-Baqarah English Tafseer text is seven [4]- [6], [21]. Therefore, (K=7) is used for the three algorithms of the research experiments.…”