书目名称 | Machine Learning Methods for Stylometry | 副标题 | Authorship Attributi | 编辑 | Jacques Savoy | 视频video | | 概述 | Presents various machine-learning models used to solve various stylometric questions like authorship attribution, author profiling, or detecting fake news.Illustrates the approaches discussed using th | 图书封面 |  | 描述 | .This book presents methods and approaches used to identify the true author of a doubtful document or text excerpt. It provides a broad introduction to all text categorization problems (like authorship attribution, psychological traits of the author, detecting fake news, etc.) grounded in stylistic features. Specifically, machine learning models as valuable tools for verifying hypotheses or revealing significant patterns hidden in datasets are presented in detail. Stylometry is a multi-disciplinary field combining linguistics with both statistics and computer science...The content is divided into three parts. The first, which consists of the first three chapters, offers a general introduction to stylometry, its potential applications and limitations. Further, it introduces the ongoing example used to illustrate the concepts discussed throughout the remainder of the book. The four chapters of the second part are more devoted to computer science with a focus on machine learningmodels. Their main aim is to explain machine learning models for solving stylometric problems. Several general strategies used to identify, extract, select, and represent stylistic markers are explained. As dee | 出版日期 | Book 2020 | 关键词 | Stylometry; Natural Language Processing; Information Retrieval; Machine Learning; Quantitative Linguisti | 版次 | 1 | doi | https://doi.org/10.1007/978-3-030-53360-1 | isbn_ebook | 978-3-030-53360-1 | copyright | Springer Nature Switzerland AG 2020 |
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