C 2025

Utilization of LLM for Process Mining Analysis of Event Log of Travel Expenses at the Operational Level

HALAŠKA, Michal and Roman ŠPERKA

Basic information

Original name

Utilization of LLM for Process Mining Analysis of Event Log of Travel Expenses at the Operational Level

Authors

HALAŠKA, Michal (203 Czech Republic, belonging to the institution) and Roman ŠPERKA (703 Slovakia, guarantor, belonging to the institution)

Edition

1. vyd. London, Utilization of LLM for Process Mining Analysis of Event Log of Travel Expenses at the Operational Level, p. 57-79, 23 pp. AI, Analytics and Strategic Decision-Making, 2025

Publisher

Routledge

Other information

Language

English

Type of outcome

Chapter(s) of a specialized book

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

is not subject to a state or trade secret

Publication form

printed version "print"

References:

URL

Organization unit

School of Business Administration in Karvina

ISBN

978-1-032-83110-7

DOI

https://doi.org/10.4324/9781003507840

Keywords in English

ChatGPT; BPM; LLM; travel expanses; process mining

Tags

International impact, Reviewed
Changed: 2/8/2025 08:47, doc. RNDr. Ing. Roman Šperka, Ph.D.

Abstract

In the original language

This chapter explores the application of large language models (LLMs) in process mining, mainly focusing on their ability to manage complex queries and interpret processes effectively. It aims to identify which business process management (BPM) tasks LLMs can support and the potential transformative impact on BPM workflows. The study uses ChatGPT, a state-of-the-art LLM, to analyze an event log of travel expenses at a university. A series of prompts are designed to evaluate the model’s performance in extracting process descriptions, identifying anomalies, and generating process insights. The findings demonstrate ChatGPT’s proficiency in transforming complex process mining data into intuitive formats, significantly improving the efficiency and precision of process analysis. The model successfully identified process variants, anomalies, and bottlenecks and provided detailed descriptions of process activities. Integrating conversational AI like ChatGPT into process mining can make these tools more accessible and effective, reducing the need for specialized expertise. This integration has the potential to improve traditional process mining techniques, leading to more insightful and actionable results in BPM. This chapter provides a preliminary exploration of the applicability in process mining, offering valuable information on their potential to transform BPM practices. It highlights the innovative use of conversational AI to complement and enhance existing process mining methodologies. The study underscores the need for further research to validate these findings and explore advanced AI technologies for process optimization.
Displayed: 27/10/2025 23:46