| Summary: | This article presents an novel approach inspired by the modern exploration of short texts’ patterning to creations prescribed to the outstanding Islamic jurist, theologian, and mystical thinker Abu Hamid Al Ghazali. We treat the task with the general authorship attribution problematics and employ a Convolutional Neural Network (CNN), intended in combination with a balancing procedure to recognize short, concise templates in manuscripts. The proposed system suggests new attitudes make it possible to investigate medieval Arabic documents from a novel computational perspective. An evaluation of the results on a previously tagged collection of books ascribed to Al Ghazali demonstrates the method’s high reliability in recognizing the source authorship. Evaluations of two famous manuscripts, <i>Mishakat al-Anwa</i> and <i>Tahafut al-Falasifa</i>, questioningly attributed to Al Ghazali or co-authored by him, exhibit a significant difference in their overall stylistic style with one inherently assigned to Al Ghazali. This fact can serve as a substantial formal argument in the long-standing dispute about these manuscripts’ authorship. The proposed methodology suggests a new look on the perusal of medieval documents’ inner structures and possible authorship from the short-patterning and signal processing perspectives.
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