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Searching Quran Chapters Verses Weight with TF and Pareto Principle to Support Memorizing (Case Study Juz ‘Amma)

机译:使用TF和Pareto原理搜索《古兰经》章节的权重以支持记忆(案例研究Juz’Amma)

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Quran is holy book for Moslems. Reading it, understanding its meaning, even memorizing it is very useful. But memorizing 6236 of its verses is not an easy task, even short juz `amma chapters. Several memorizing methods have been known. In panipati, Turkey, Mauritanian, Singapore method, students memorize Quran page by page, from first juz or last juz. In Sudan, students memorize verses with writing its out. In mnemonic learning, verses are linked with the association. Photographic memory is used to recall an image of verses in any page. From computing theory, especially artificial intelligence, Breadth First Search algorithm can be hoped to support memorizing Quran. Memorize its chapter title, what the main topic, memorize verses that tell it, then expand to previously or next verses. Another method is using statistic, using Term Frequency (TF) to get list verses in each chapter of Juz `Amma that its weight of term at least is eighty percent of chapter weight of term. With minimum verses, student has memorized most important verses in each chapter.
机译:古兰经是穆斯林的圣书。阅读它,理解它的含义,甚至记住它是非常有用的。但是,记住6236的经文并不是一件容易的事,即使短短的amma章节也是如此。几种记忆方法是已知的。在Panipati,土耳其,毛里塔尼亚,新加坡的方法中,学生从头一个juz或最后一个juz逐页地记住古兰经。在苏丹,学生通过写下来背诵经文。在助记符学习中,经文与联想联系在一起。摄影存储器用于调出任何页面中的经文图像。从计算理论(尤其是人工智能)来看,广度优先搜索算法可以支持记忆古兰经。记住其章节标题(主要主题),记住讲述该主题的经文,然后扩展到上一个或下一个经文。另一种方法是使用统计,即使用术语频率(TF)获取Juz`Amma每一章中的列表经文,其术语权重至少为术语章节权重的80%。通过最少的经文,学生在每一章中都记住了最重要的经文。

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