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ProcessExplorer: Interactive Visual Exploration of Event Logs with Analysis Guidance

Seeliger, Alexander ; Ratzke, Maximilian ; Nolle, Timo ; Mühlhäuser, Max
Burattin, Andrea ; Polyvyanyy, Artem ; Zelst, Sebastiaan van (eds.) (2019):
ProcessExplorer: Interactive Visual Exploration of Event Logs with Analysis Guidance.
In: 1st International Conference on Process Mining - Demo Track, pp. 24-27,
Aachen, Germany, ICPMD 2019, Aachen, Germany, June 24-26, 2019, [Conference or Workshop Item]

Abstract

Process analysts use process mining techniques to obtain fact-based knowledge from event logs about how business processes are actually executed in organizations. Often process discovery is the first step in their analytical workflow. However, when working with large amount of data and complex processes, exploring as-is process models to obtain interesting and insightful knowledge can be challenging. We propose ProcessExplorer, an interactive visual recommendation system for process discovery to ease event log exploration. ProcessExplorer automatically analyzes the event log to obtain promising subsets of cases, evaluates interesting process performance indicators, and recommends those that are most interesting and insightful. Our system uses multi-perspective trace clustering to identify candidate cases of interest and a deviation-based approach to assess the interestingness of process performance indicators. We implemented ProcessExplorer as a standalone desktop application that allows to explore any process and any event log. Our demo shows how the workflow of analysts is supported by the system through suggesting subset and insights recommendations.

Item Type: Conference or Workshop Item
Erschienen: 2019
Editors: Burattin, Andrea ; Polyvyanyy, Artem ; Zelst, Sebastiaan van
Creators: Seeliger, Alexander ; Ratzke, Maximilian ; Nolle, Timo ; Mühlhäuser, Max
Title: ProcessExplorer: Interactive Visual Exploration of Event Logs with Analysis Guidance
Language: English
Abstract:

Process analysts use process mining techniques to obtain fact-based knowledge from event logs about how business processes are actually executed in organizations. Often process discovery is the first step in their analytical workflow. However, when working with large amount of data and complex processes, exploring as-is process models to obtain interesting and insightful knowledge can be challenging. We propose ProcessExplorer, an interactive visual recommendation system for process discovery to ease event log exploration. ProcessExplorer automatically analyzes the event log to obtain promising subsets of cases, evaluates interesting process performance indicators, and recommends those that are most interesting and insightful. Our system uses multi-perspective trace clustering to identify candidate cases of interest and a deviation-based approach to assess the interestingness of process performance indicators. We implemented ProcessExplorer as a standalone desktop application that allows to explore any process and any event log. Our demo shows how the workflow of analysts is supported by the system through suggesting subset and insights recommendations.

Journal or Publication Title: 1st International Conference on Process Mining
Book Title: 1st International Conference on Process Mining - Demo Track
Place of Publication: Aachen, Germany
Uncontrolled Keywords: process discovery, variants analysis, log pre-processing, trace clustering, statistical hypothesis testing
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Telecooperation
Event Title: ICPMD 2019
Event Location: Aachen, Germany
Event Dates: June 24-26, 2019
Date Deposited: 06 May 2019 11:01
URL / URN: http://ceur-ws.org/Vol-2374/paper7.pdf
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