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Applying Predictive Process Monitoring to Predict User Behavior with Click Data Behavior with Click Data - Short Paper

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dc.contributor.authorFeiler, Jana
dc.contributor.authorWalter, Tobias
dc.contributor.editorMarkus Böhm, Jürgen Wunderlich
dc.date.accessioned2024-10-01T10:15:41Z
dc.date.available2024-10-01T10:15:41Z
dc.date.issued2024
dc.description.abstractPredictive 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.doi10.18420/AKWI2024-017
dc.identifier.isbn978-3-88579-801-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44656
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofAKWI Jahrestagung 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-357
dc.subjectProcess Mining
dc.subjectPredictive Process Monitoring
dc.subjectUnstructured Business Processes
dc.subjectClick Data
dc.subjectUser Behavior Analysis
dc.titleApplying Predictive Process Monitoring to Predict User Behavior with Click Data Behavior with Click Data - Short Paperen
dc.typeText/Conference Paper
gi.citation.endPage199
gi.citation.publisherPlaceBonn
gi.citation.startPage193
gi.conference.date09.-10.09.2024
gi.conference.locationHAW-Landshut
gi.conference.sessiontitlePoster Presentations

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