Process mining (PM) comprises a variety of methods for discovering information about
processes from their execution logs. Some of them, such as trace clustering, trace …

Encoding methods are employed across several process mining tasks, including predictive
process monitoring, anomalous case detection, trace clustering, etc. These methods are …

This technical report describes the intersection of process mining and large language
models (LLMs), specifically focusing on the abstraction of traditional and object-centric …

Conformance checking refers to techniques that can compare normative process behavior,
typically captured by process models, and observed process behavior, usually captured in …

Since the first version of the Entity–Relationship (ER) model proposed by Peter Chen over
forty years ago, both the ER model and conceptual modeling activities have been key …

In this paper, we propose a novel predictive process monitoring approach, named JARVIS,
that is designed to achieve a balance between accuracy and explainability in the task of next …

Process mining techniques have proven crucial in identifying performance and compliance
issues. Traditional process mining, however, is primarily case-centric and does not fully …

Trace clustering has been extensively used to discover aspects of the data from event logs.
Process Mining techniques guide the identification of sub-logs by grouping traces with …

Business processes are often monitored by transactional information systems that produce
massive dataset called event logs. Such logs contain the process execution traces, typically …

Anomalous traces diminish the event log's quality due to bad execution or security issues,
for instance. Focusing on mitigating this phenomenon, organizations spend efforts to detect …