{"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/distributed-online-learning-of-event","title":"Distributed Online Learning of Event Definitions","arxiv_id":"1705.02175","date":"2017-05-05","proceeding":null,"authors":["Nikos Katzouris","Alexander Artikis","Georgios Paliouras"],"abstract":"Logic-based event recognition systems infer occurrences of events in time\nusing a set of event definitions in the form of first-order rules. The Event\nCalculus is a temporal logic that has been used as a basis in event recognition\napplications, providing among others, direct connections to machine learning,\nvia Inductive Logic Programming (ILP). OLED is a recently proposed ILP system\nthat learns event definitions in the form of Event Calculus theories, in a\nsingle pass over a data stream. In this work we present a version of OLED that\nallows for distributed, online learning. We evaluate our approach on a\nbenchmark activity recognition dataset and show that we can significantly\nreduce training times, exchanging minimal information between processing nodes.","url_abs":"http://arxiv.org/abs/1705.02175v1","url_pdf":"http://arxiv.org/pdf/1705.02175v1.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":"distributed-online-learning-of-event","repo_url":"https://github.com/nkatzz/OLED","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"activity-recognition","task_name":"Activity Recognition"},{"task_slug":"form","task_name":"Form"},{"task_slug":"inductive-logic-programming","task_name":"Inductive logic programming"}],"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}