{"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/generating-memorable-mnemonic-encodings-of","title":"Generating Memorable Mnemonic Encodings of Numbers","arxiv_id":"1705.02700","date":"2017-05-07","proceeding":null,"authors":["Vincent Fiorentini","Megan Shao","Julie Medero"],"abstract":"The major system is a mnemonic system that can be used to memorize sequences\nof numbers. In this work, we present a method to automatically generate\nsentences that encode a given number. We propose several encoding models and\ncompare the most promising ones in a password memorability study. The results\nof the study show that a model combining part-of-speech sentence templates with\nan $n$-gram language model produces the most memorable password\nrepresentations.","url_abs":"http://arxiv.org/abs/1705.02700v1","url_pdf":"http://arxiv.org/pdf/1705.02700v1.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":"generating-memorable-mnemonic-encodings-of","repo_url":"https://github.com/VinceFior/major-system","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}