Interactive log-delta analysis using multi-range filtering

Vidgof, Maxim ORCID: https://orcid.org/0000-0003-2394-2247 and Djurica, Djordje ORCID: https://orcid.org/0000-0002-3656-8314 and Bala, Saimir ORCID: https://orcid.org/0000-0001-7179-1901 and Mendling, Jan (2021) Interactive log-delta analysis using multi-range filtering. Software and Systems Modeling. ISSN 1619-1366

[img]
Preview
Text
Vidgof2021_Article_InteractiveLog-deltaAnalysisUs.pdf
Available under License Creative Commons: Attribution 4.0 International (CC BY 4.0).

Download (2MB) | Preview

Abstract

Process mining is a family of analytical techniques that extract insights from an event log and present them to an analyst. A key analysis task is to understand the distinctive features of different variants of the process and their impact on process performance. Techniques for log-delta analysis (or variant analysis) put a strong emphasis on automatically extracting explanations for differences between variants. A weakness of them is, however, their limited support for interactively exploring the dividing line between typical and atypical behavior. In this paper, we address this research gap by developing and evaluating an interactive technique for log-delta analysis, which we call InterLog. This technique is developed based on the idea that the analyst can interactively define filter ranges and that these filters are used to partition the log L into sub-logs L1 for the selected cases and L2 for the deselected cases. In this way, the analyst can step-by-step explore the log and manually separate the typical behavior from the atypical. We prototypically implement InterLog and demonstrate its application for a real-world event log. Furthermore, we evaluate it in a preliminary design study with process mining experts for usefulness and ease of use.

Item Type: Article
Keywords: Process mining, Log-delta analysis, Variant analysis, Multi-range filter, Event logs, Event sequence data
Divisions: Departments > Wirtschaftsinformatik u. Operations Mgmt > Data, Process and Knowledge Management > Informationswirtschaft
Version of the Document: Published
Depositing User: ePub Administrator
Date Deposited: 28 Sep 2021 15:14
Last Modified: 20 Oct 2021 11:53
Related URLs:
FIDES Link: https://bach.wu.ac.at/d/research/results/101676/
URI: https://epub.wu.ac.at/id/eprint/8314

Actions

View Item View Item

Downloads

Downloads per month over past year

View more statistics