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ProcessExplorer: Intelligent Process Mining Guidance

Seeliger, Alexander and Sánchez Guinea, Alejandro and Nolle, Timo and Mühlhäuser, Max (2019):
ProcessExplorer: Intelligent Process Mining Guidance.
In: 17th International Conference on Business Process Management, Wien, Austria, DOI: 10.1007/978-3-030-26619-6_15,
[Online-Edition: https://link.springer.com/chapter/10.1007/978-3-030-26619-6_...],
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Seeliger, Alexander and Sánchez Guinea, Alejandro and Nolle, Timo and Mühlhäuser, Max
Title: ProcessExplorer: Intelligent Process Mining Guidance
Language: English
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.

Journal or Publication Title: 17th International Conference on Business Process Management
Title of Book: 17th International Conference on Business Process Management
Place of Publication: Wien, Austria
Edition: 17
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Telecooperation
Date Deposited: 08 May 2019 07:14
DOI: 10.1007/978-3-030-26619-6_15
Official URL: https://link.springer.com/chapter/10.1007/978-3-030-26619-6_...
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