Stylomech：通过英语与罗马化僧伽罗语中的计算文体学揭示作者身份
Stylomech: Unveiling Authorship via Computational Stylometry in English and Romanized Sinhala
AI总结：
本文提出 Stylomech 作者归属系统，利用作者文本对的数值表示而非大型语料库进行训练，以解决英语和罗马化僧伽罗语中的作者识别与内容验证问题。
摘要：
随着 Web 2.0 的出现，社交技术的发展与全球通信相结合，系统性地给社会带来了正面和负面影响。由于社会缺乏适当的伦理规范，内容侵权行为大量增加，因此版权主张和作者识别被认为至关重要。在过去几十年中，英语和罗马化僧伽罗语中的作者归属成为一项重要需求。作为一个在很大程度上尚未得到探索的领域，尤其是在罗马化僧伽罗语语境下，本研究对计算语言学领域作出了重要贡献。所提出的作者归属系统提供了一种独特方法，仅允许比较两组文本：嫌疑作者文本和匿名文本，这不同于通常依赖大型语料库的传统方法。本工作侧重于使用同一作者和不同作者的各种文本对的数值表示，使模型基于这些表示而非文本进行训练；只要嫌疑作者文本和匿名文本具有合理质量，这就使其能够适用于众多作者和语境。通过将作者归属的范围扩展到涵盖多样的语言语境，本工作有助于促进数字通信中的信任与问责，尤其是在斯里兰卡。本研究提出了一种面向英语和罗马化僧伽罗语作者归属的开创性方法，满足了数字时代内容验证和知识产权执法方面的关键需求。
英文摘要：
With the advent of Web 2.0, the development in social technology coupled with global communication systematically brought positive and negative impacts to society. Copyright claims and Author identification are deemed crucial as there has been a considerable amount of increase in content violation owing to the lack of proper ethics in society. The Author's attribution in both English and Romanized Sinhala became a major requirement in the last few decades. As an area largely unexplored, particularly within the context of Romanized Sinhala, the research contributes significantly to the field of computational linguistics. The proposed author attribution system offers a unique approach, allowing for the comparison of only two sets of text: suspect author and anonymous text, a departure from traditional methodologies which often rely on larger corpora. This work focuses on using the numerical representation of various pairs of the same and different authors allowing for, the model to train on these representations as opposed to text, this allows for it to apply to a multitude of authors and contexts, given that the suspected author text, and the anonymous text are of reasonable quality. By expanding the scope of authorship attribution to encompass diverse linguistic contexts, the work contributes to fostering trust and accountability in digital communication, especially in Sri Lanka. This research presents a pioneering approach to author attribution in both English and Romanized Sinhala, addressing a critical need for content verification and intellectual property rights enforcement in the digital age.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
