{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:06:23Z","timestamp":1774915583643,"version":"3.50.1"},"reference-count":15,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T00:00:00Z","timestamp":1698019200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T00:00:00Z","timestamp":1698019200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,23]]},"DOI":"10.1109\/icpm60904.2023.10271960","type":"proceedings-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T18:20:51Z","timestamp":1696875651000},"page":"105-112","source":"Crossref","is-referenced-by-count":2,"title":["Measuring the Stability of Process Outcome Predictions in Online Settings"],"prefix":"10.1109","author":[{"given":"Suhwan","family":"Lee","sequence":"first","affiliation":[{"name":"Utrecht University,Utrecht,The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Comuzzi","sequence":"additional","affiliation":[{"name":"Ulsan National Institute of Science and Technology,Ulsan,Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xixi","family":"Lu","sequence":"additional","affiliation":[{"name":"Utrecht University,Utrecht,The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hajo A.","family":"Reijers","sequence":"additional","affiliation":[{"name":"Utrecht University,Utrecht,The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-05760-1_15"},{"key":"ref15","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume":"32","author":"paszke","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref14","first-page":"4945","article-title":"River: machine learning for streaming data in python","volume":"22","author":"montiel","year":"2021","journal-title":"The Journal of Machine Learning Research"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/347090.347107"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-03915-7_22"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-85469-0_10"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91704-7_2"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3301300"},{"key":"ref7","first-page":"297","article-title":"Complex symbolic sequence encodings for predictive monitoring of business processes","author":"leontjeva","year":"2016","journal-title":"International Conference on Business Process Management"},{"key":"ref9","first-page":"406","article-title":"Fast and accurate business process drift detection","author":"maaradji","year":"2016","journal-title":"International Conference on Business Process Management"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CBI49978.2020.00016"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/SCC.2017.10"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-98581-3_18"},{"key":"ref5","article-title":"Incremental predictive process monitoring: How to deal with the variability of real environments","author":"di francescomarino","year":"2018"}],"event":{"name":"2023 5th International Conference on Process Mining (ICPM)","location":"Rome, Italy","start":{"date-parts":[[2023,10,23]]},"end":{"date-parts":[[2023,10,27]]}},"container-title":["2023 5th International Conference on Process Mining (ICPM)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10271932\/10271938\/10271960.pdf?arnumber=10271960","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,30]],"date-time":"2023-10-30T18:38:08Z","timestamp":1698691088000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10271960\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,23]]},"references-count":15,"URL":"https:\/\/doi.org\/10.1109\/icpm60904.2023.10271960","relation":{},"subject":[],"published":{"date-parts":[[2023,10,23]]}}}