{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/authorship-attribution-using-the-chaos-game","title":"Authorship Attribution Using the Chaos Game Representation","arxiv_id":"1802.06007","date":"2018-02-14","proceeding":null,"authors":["Daniel Lichtblau","Catalin Stoean"],"abstract":"The Chaos Game Representation, a method for creating images from nucleotide\nsequences, is modified to make images from chunks of text documents. Machine\nlearning methods are then applied to train classifiers based on authorship.\nExperiments are conducted on several benchmark data sets in English, including\nthe widely used Federalist Papers, and one in Portuguese. Validation results\nfor the trained classifiers are competitive with the best methods in prior\nliterature. The methodology is also successfully applied for text\ncategorization with encouraging results. One classifier method is moreover seen\nto hold promise for the task of digital fingerprinting.","url_abs":"http://arxiv.org/abs/1802.06007v1","url_pdf":"http://arxiv.org/pdf/1802.06007v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"authorship-attribution-using-the-chaos-game","repo_url":"https://github.com/catalinstoean/FCGR-LR","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"authorship-attribution","task_name":"Authorship Attribution"},{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"text-categorization","task_name":"Text Categorization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}