Applying Predictive Process Monitoring to Predict User Behavior with Click Data Behavior with Click Data - Short Paper
| dc.contributor.author | Feiler, Jana | |
| dc.contributor.author | Walter, Tobias | |
| dc.contributor.editor | Markus Böhm, Jürgen Wunderlich | |
| dc.date.accessioned | 2024-10-01T10:15:41Z | |
| dc.date.available | 2024-10-01T10:15:41Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Predictive Process Monitoring (PPM) is used to predict the future behavior of running process instances using machine learning techniques. While traditional PPM focuses and works well on highly structured business processes, the planned research explores the application of and challenges related to PPM on rather unstructured processes, such as those discovered through user click traces on websites. Therefore, this resarch’s overall objective is to develop and evaluate appropriate AI-supported PPM approaches for unstructured processes based on click traces provided by Germany’s public broadcaster ARD with its audio and video streaming services ARD Mediathek & ARD Audiothek. | en |
| dc.identifier.doi | 10.18420/AKWI2024-017 | |
| dc.identifier.isbn | 978-3-88579-801-9 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/44656 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | AKWI Jahrestagung 2024 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-357 | |
| dc.subject | Process Mining | |
| dc.subject | Predictive Process Monitoring | |
| dc.subject | Unstructured Business Processes | |
| dc.subject | Click Data | |
| dc.subject | User Behavior Analysis | |
| dc.title | Applying Predictive Process Monitoring to Predict User Behavior with Click Data Behavior with Click Data - Short Paper | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 199 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 193 | |
| gi.conference.date | 09.-10.09.2024 | |
| gi.conference.location | HAW-Landshut | |
| gi.conference.sessiontitle | Poster Presentations |
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