基于视觉分析的《古兰经》作者身份调查

H. Sayoud
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引用次数: 9

摘要

在本文中,我们提出了一种基于视觉分析的调查,以确定神圣古兰经的作者身份,并将其与圣训作者(先知)联系起来。这可以被看作是古兰经和圣训这两本宗教书籍的作者区分任务。第一本书代表了先知穆罕默德所声称的由安拉(上帝)写的神圣的书,而第二本书代表了经认证的先知陈述的集合。采用了两种可视化分析聚类方法,即层次聚类和模糊均值聚类。另一方面,在分类过程之前,将七种类型的NLP特征进行组合和归一化PCA约简。可视化分析结果揭示了2D和3D配置的有趣结果。总之,他们在两个实验中都显示了两个主要集群:《古兰经》集群和《圣训》集群;和处置由此产生的集群对应于一个明确的作者区分之间的两个宗教书籍。
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A Visual Analytics based Investigation on the Authorship of the Holy Quran
In this paper, we present a visual analytics based investigation for the task of authorship attribution of the holy Quran with regards to the Hadith Author (the Prophet). This can be seen as an authorship discrimination task between the two religious books: Quran vs Hadith. The first book represents the Divine book written by Allah (God) as claimed by the Prophet Muhammad, whereas the second one represents a collection of certified Prophet’s statements. Two visual analytics clustering methods are employed, namely: a Hierarchical Clustering and Fuzzy Cmean Clustering. On the other hand, seven types of NLP features are combined and normalized by PCA reduction before the classification process. The visual analytics results have revealed interesting results in 2D and 3D disposition. In summary, they show two main clusters in both experiments: Quran cluster and Hadith cluster; and the disposition of the resulting clusters corresponds to a clear authorship distinction between the two religious books.
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