用计算方法验证但丁真作争议文本，准确率达97%
The \textit{Questio de aqua et terra}: A Computational Authorship Verification Study
- 构建多模型系统，结合机器学习与文体分析
- 最佳模型在330篇拉丁文文本上达F1=0.970
- 首次应用分布随机过采样提升鉴定精度
《Questio de aqua et terra》是一篇传统上归于但丁·阿利吉耶里的宇宙学著作，但其真实性存在争议，因与但丁已知作品不符且缺乏同时代记载。本研究通过计算作者身份验证（AV）技术，对文本真伪进行分析。我们构建了一套AV系统，并建立包含330篇13至14世纪拉丁文文本的语料库，采用留一法交叉验证进行对比评估。最佳系统在文本体裁异质性背景下仍实现高验证准确率（F1=0.970）。关键贡献在于引入分布随机过采样（DRO），该技术此前未用于作者身份验证，显著提升了性能。将该系统应用于《Questio》，得出高度可信的真伪判断。研究为该文本作者归属争议提供新证据，并凸显DRO在文化遗产分析中的潜力。
原文摘要 · Abstract (English)
The Questio de aqua et terra is a cosmological treatise traditionally attributed to Dante Alighieri. However, the authenticity of this text is controversial, due to discrepancies with Dante's established works and to the absence of contemporary references. This study investigates the authenticity of the Questio via computational authorship verification (AV), a class of techniques which combine supervised machine learning and stylometry. We build a family of AV systems and assemble a corpus of 330 13th- and 14th-century Latin texts, which we use to comparatively evaluate the AV systems through leave-one-out cross-validation. Our best-performing system achieves high verification accuracy (F1=0.970) despite the heterogeneity of the corpus in terms of textual genre. The key contribution to the accuracy of this system is shown to come from Distributional Random Oversampling (DRO), a technique specially tailored to text classification which is here used for the first time in AV. The application of the AV system to the Questio returns a highly confident prediction concerning its authenticity. These findings contribute to the debate on the authorship of the Questio, and highlight DRO's potential in the application of AV to cultural heritage.
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