{"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/outcome-oriented-predictive-process","title":"Outcome-Oriented Predictive Process Monitoring: Review and Benchmark","arxiv_id":"1707.06766","date":"2017-07-21","proceeding":null,"authors":["Irene Teinemaa","Marlon Dumas","Marcello La Rosa","Fabrizio Maria Maggi"],"abstract":"Predictive business process monitoring refers to the act of making\npredictions about the future state of ongoing cases of a business process,\nbased on their incomplete execution traces and logs of historical (completed)\ntraces. Motivated by the increasingly pervasive availability of fine-grained\nevent data about business process executions, the problem of predictive process\nmonitoring has received substantial attention in the past years. In particular,\na considerable number of methods have been put forward to address the problem\nof outcome-oriented predictive process monitoring, which refers to classifying\neach ongoing case of a process according to a given set of possible categorical\noutcomes - e.g., Will the customer complain or not? Will an order be delivered,\ncanceled or withdrawn? Unfortunately, different authors have used different\ndatasets, experimental settings, evaluation measures and baselines to assess\ntheir proposals, resulting in poor comparability and an unclear picture of the\nrelative merits and applicability of different methods. To address this gap,\nthis article presents a systematic review and taxonomy of outcome-oriented\npredictive process monitoring methods, and a comparative experimental\nevaluation of eleven representative methods using a benchmark covering 24\npredictive process monitoring tasks based on nine real-life event logs.","url_abs":"http://arxiv.org/abs/1707.06766v4","url_pdf":"http://arxiv.org/pdf/1707.06766v4.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":"outcome-oriented-predictive-process","repo_url":"https://github.com/irhete/predictive-monitoring-benchmark","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"predictive-process-monitoring","task_name":"Predictive Process Monitoring"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}