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，用于评估，测试，和作者归因技术的交叉应用/ / Patrick M. Juola博士，杜肯大学文档不只是谈论它们的内容；对于训练有素的人来说，它们也能透露出很多关于作者的信息。几个世纪以来，人文学科的“作者归属”领域一直在关注这个问题，试图确定如何确定一份文件的作者，以及确定作者的准确性。语料库语言学的最新发展表明，通过“非传统”的方法，即对单词、短语、布局和文件的其他特征进行统计调查，自动做出这些决定是可能的。不幸的是，目前最先进的技术是一堆被提议的方法的混乱集合，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，以模块化设计来执行此任务，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结果集（新颖的）组合，项目建立了各种技术（在各种测试条件下）的准确性基准，发现了导致技术改进的新组合，并创建了“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."