Being around for decades, the problem of Authorship Attribution is still very
much in focus currently. Some of the more recent instruments used are the
pre-trained language models, the most prevalent being BERT. Here we used such a
model to detect the authorship of texts written in the Romanian language. The
dataset used is highly unbalanced, i.e., significant differences in the number
of texts per author, the sources from which the texts were collected, the time
period in which the authors lived and wrote these texts, the medium intended to
be read (i.e., paper or online), and the type of writing (i.e., stories, short
stories, fairy tales, novels, literary articles, and sketches). The results are
better than expected, sometimes exceeding 87\% macro-accuracy.

使用预训练的语言模型 BERT 来检测罗马尼亚语文本的作者，虽然数据集不平衡，但结果比预期好，有时超过 87％的宏平均精度。

基于 BERT 的罗马尼亚语数据集 ROST 的作者归属

BERT-based Authorship Attribution on the Romanian Dataset called ROST

Determining the author of a text is a difficult task. Here we compare
multiple AI techniques for classifying literary texts written by multiple
authors by taking into account a limited number of speech parts (prepositions,
adverbs, and conjunctions). We also introduce a new dataset composed of texts
written in the Romanian language on which we have run the algorithms. The
compared methods are Artificial Neural Networks, Support Vector Machines, Multi
Expression Programming, Decision Trees with C5.0, and k-Nearest Neighbour.
Numerical experiments show, first of all, that the problem is difficult, but
some algorithms are able to generate decent errors on the test set.

本文探讨了利用人工智能技术对多个作者编写的文学文本进行分类的难点，并介绍了一个新的包含罗马尼亚语文本的数据集。经过数值实验比较，得出了人工神经网络、支持向量机、多表达式编程、决策树以及 k - 最近邻等算法在测试集上表现较好。

比较几种 AI 技术用于罗马尼亚文本的作者识别

A comparison of several AI techniques for authorship attribution on Romanian texts

We present RONEC - the Named Entity Corpus for the Romanian language. The
corpus contains over 26000 entities in ~5000 annotated sentences, belonging to
16 distinct classes. The sentences have been extracted from a copy-right free
newspaper, covering several styles. This corpus represents the first initiative
in the Romanian language space specifically targeted for named entity
recognition. It is available in BRAT and CoNLL-U Plus formats, and it is free
to use and extend at github.com/dumitrescustefan/ronec .

介绍了适用于罗马尼亚语的 RONEC 命名实体语料库，该语料库包含 26000 多个实体，在约 5000 个带注释的句子中属于 16 个不同的类别，是罗马尼亚语领域指定的第一个命名实体识别语料库之一，可用于 BRAT 和 CoNLL-U Plus 格式，且可在 github.com/dumitrescustefan/ronec 上自由使用和扩展。