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Taking advantage of Turkish characteristic features to achieve authorship attribution problems for Turkish

机译:充分利用土耳其语的特色功能来解决土耳其语的作者归属问题

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The rapid increase in the number of the electronic and online texts such as electronic mails, online newspapers and magazines, blog posts and online forum messages has also accelerated the studies carried out on authorship attribution. Although the studies are not as abundant as in English language, there have been considerable studies on author identification in Turkish in the last fifteen years. This study includes two parts; first part is a quick review of Turkish authorship attribution studies. The review is focused on the stylometric features that enable authors to be distinguished one from another. In the second part, we analyze the main characteristics of the Turkish Language and depict our first experiments on Turkish corpora. We experiment taking advantages of Turkish characteristic features by using frequencies of gerunds, and use Support Vector Machines as learning algorithm.
机译:电子和在线文本(例如电子邮件,在线报纸和杂志,博客文章和在线论坛消息)的数量迅速增加,也加快了关于作者身份归属的研究。尽管研究不如英语丰富,但在过去的十五年中,土耳其人对作者身份的研究已经很多。这项研究包括两个部分:第一部分是对土耳其作者身份归因研究的快速回顾。这篇综述着重于使作者与众不同的风格特征。在第二部分中,我们分析了土耳其语的主要特征,并描述了我们在土耳其语料库上的第一个实验。我们尝试通过使用动名词频率来利用土耳其特征的优势,并使用支持向量机作为学习算法。

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