SDCI Data New: A Modular Software Framework for Evaluation, Testing, and Cross-Fertilization of Authorship Attribution Techniques

一个模块化的软件框架，用于作者归属技术的评估、测试和交叉施肥。迪克讷大学朱奥拉博士文件不仅仅是在谈论它们的内容;对一个训练有素的人来说，它们还可以说很多关于它们的作者的事情。 人文学科的“作者归属”领域几个世纪以来一直致力于此，试图确定如何以及如何准确地确定一份文件的作者。 语料库语言学的最新发展表明，可以通过“非传统”方法自动进行这些确定，基本上是对单词、短语、布局和文档的其他特征进行统计调查。不幸的是，目前最先进的是一个混乱的建议方法的集合，几乎没有关于哪些方法有效，为什么有效以及在什么条件下最有效的指导。 我们正在通过开发一个模块化软件框架（使用Juola[23]提出的理论模型）来解决这个问题，以便在模块化设计中执行这项任务，该设计允许在交叉组合中轻松交换功能组件。通过将严格的测试方法应用于（新）组合的结果集，该项目正在为各种技术（在各种测试条件下）建立准确性基准，寻找导致改进技术的新组合，并创建“最佳实践”。"

A Modular Software Framework for Evaluation, Testing, and Cross-Fertilization of Authorship Attribution TechniquesPI: Patrick M. Juola, PhD, Duquesne UniversityDocuments do not speak only of their contents; to a trained eye, they can also say much about their author. The field of ``authorship attribution'' in humanities scholarship has been attending to this for centuries, trying to determine how and to what accuracy the author of a document can be determined. Recent developments in corpus linguistics have shown it to be possible to make these determinations automatically by ``non-traditional'' methods, essentially statistical investigations of the words, phrases, layout, and other features of the document. Unfortunately, the current state-of-the-art is a confused collection of proposed methods, with little guidance about which methods work, why they work, and under what conditions they work best. We are addressing this by developing a modular software framework (using a theoretical model proposed by Juola[23]) to perform this task in a modular design that permits easy swapping of functional components in cross-combination. By applying a rigorous testing method to the resulting set of (novel) combinations, the project is establishing accuracy benchmarks for various techniques (under the various testing conditions), finding new combinations resulting in improved techniques, and creating "best practices."