PM-LLM-Benchmark: Evaluating large language models on process mining tasks
Large Language Models (LLMs) have the potential to semi-automate some process mining
(PM) analyses. While commercial models are already adequate for many analytics tasks, the …
(PM) analyses. While commercial models are already adequate for many analytics tasks, the …
PM4Py. LLM: a Comprehensive Module for Implementing PM on LLMs
A Berti - arXiv preprint arXiv:2404.06035, 2024 - arxiv.org
pm4py is a process mining library for Python implementing several process mining (PM)
artifacts and algorithms. It also offers methods to integrate PM with large language models …
artifacts and algorithms. It also offers methods to integrate PM with large language models …
Challenges of Anomaly Detection in the Object-Centric Setting: Dimensions and the Role of Domain Knowledge
Object-centric event logs, allowing events related to different objects of different object types,
represent naturally the execution of business processes, such as ERP (O2C and P2P) and …
represent naturally the execution of business processes, such as ERP (O2C and P2P) and …
Re-Thinking Process Mining in the AI-Based Agents Era
Large Language Models (LLMs) have emerged as powerful conversational interfaces, and
their application in process mining (PM) tasks has shown promising results. However, state …
their application in process mining (PM) tasks has shown promising results. However, state …
Enhanced Database Interaction Using Large Language Models for Improved Data Retrieval and Analysis
V Usha, NC Abhinash, SN Chowdary… - … on Intelligent Cyber …, 2024 - ieeexplore.ieee.org
One of the difficult task for many users on SQL is to write the SQL Query due to its syntax and
structure. If a person needs to query a database, they should know everything about how …
structure. If a person needs to query a database, they should know everything about how …
[PDF][PDF] Explainable Object-Centric Anomaly Detection: the Role of Domain Knowledge
Anomaly detection is used in process mining to identify behavior differing significantly from
the other instances. However, providing actionable insights out of the raw scores is …
the other instances. However, providing actionable insights out of the raw scores is …
[PDF][PDF] CSV-PM-LLM-Parsing: Automatic Ingestion of CSV Event Logs for Process Mining using LLMs
A Berti, WMP van der Aalst - 2024 - ceur-ws.org
This demo paper introduces CSV-PM-LLM-Parsing, a Python library to automatically
transform unstructured event logs contained in CSV files into process mining event logs by …
transform unstructured event logs contained in CSV files into process mining event logs by …