Leveraging Discourse Information Effectively for Authorship Attribution
The University of Texas at Austin（德克萨斯大学奥斯汀分校）
英文摘要：
We explore techniques to maximize the effectiveness of discourse information in the task of authorship attribution. We present a novel method to embed discourse features in a Convolutional Neural Network text classifier, which achieves a state-of-the-art result by a substantial margin. We empirically investigate several featurization methods to understand the conditions under which discourse features contribute non-trivial performance gains, and analyze discourse embeddings.
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。
