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ProcessExplorer: Intelligent Process Mining Guidance

Seeliger, Alexander ; Sánchez Guinea, Alejandro ; Nolle, Timo ; Mühlhäuser, Max (2019)
ProcessExplorer: Intelligent Process Mining Guidance.
17th International Conference on Business Process Management (BPM 2019). Wien, Austria (01.-06.09.)
doi: 10.1007/978-3-030-26619-6_15
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Large amount of data is collected in event logs from information systems, reflecting the actual execution of business processes. Due to the highly competitive pressure in the market, organizations are particularly interested in optimizing their processes. Process mining enables the extraction of valuable knowledge from event logs, such as deviations, bottlenecks, and anomalies. Due to the increase of process complexity in flexible environments, visual exploration is increasingly becoming more challenging. In this paper, we propose ProcessExplorer, an interactive process mining approach to enable fast data analysis and exploration. ProcessExplorer takes an event log as input to automatically suggest subsets of similar process behavior, evaluate each subset, generate interesting insights, and suggest the subsets with the most interesting characteristics. We implemented our approach into an interactive visual exploration system, which we use as part of a user study conducted to evaluate our approach. Our results show that ProcessExplorer can be successfully applied to analyze and explore real-life data sets efficiently.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2019
Autor(en): Seeliger, Alexander ; Sánchez Guinea, Alejandro ; Nolle, Timo ; Mühlhäuser, Max
Art des Eintrags: Bibliographie
Titel: ProcessExplorer: Intelligent Process Mining Guidance
Sprache: Englisch
Publikationsjahr: 1 September 2019
Verlag: Springer
Titel der Zeitschrift, Zeitung oder Schriftenreihe: 17th International Conference on Business Process Management
Veranstaltungstitel: 17th International Conference on Business Process Management (BPM 2019)
Veranstaltungsort: Wien, Austria
Veranstaltungsdatum: 01.-06.09.
DOI: 10.1007/978-3-030-26619-6_15
URL / URN: https://link.springer.com/chapter/10.1007/978-3-030-26619-6_...
Kurzbeschreibung (Abstract):

Large amount of data is collected in event logs from information systems, reflecting the actual execution of business processes. Due to the highly competitive pressure in the market, organizations are particularly interested in optimizing their processes. Process mining enables the extraction of valuable knowledge from event logs, such as deviations, bottlenecks, and anomalies. Due to the increase of process complexity in flexible environments, visual exploration is increasingly becoming more challenging. In this paper, we propose ProcessExplorer, an interactive process mining approach to enable fast data analysis and exploration. ProcessExplorer takes an event log as input to automatically suggest subsets of similar process behavior, evaluate each subset, generate interesting insights, and suggest the subsets with the most interesting characteristics. We implemented our approach into an interactive visual exploration system, which we use as part of a user study conducted to evaluate our approach. Our results show that ProcessExplorer can be successfully applied to analyze and explore real-life data sets efficiently.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Telekooperation
Hinterlegungsdatum: 08 Mai 2019 07:14
Letzte Änderung: 14 Jun 2021 06:14
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