Explainable concept drift in process mining
The execution of processes leaves trails of event data in information systems. These event
data are analyzed to generate insights and improvements for the underlying process …
data are analyzed to generate insights and improvements for the underlying process …
Leveraging large language models (LLMs) for process mining (Technical Report)
A Berti, MS Qafari - arXiv preprint arXiv:2307.12701, 2023 - arxiv.org
This technical report describes the intersection of process mining and large language
models (LLMs), specifically focusing on the abstraction of traditional and object-centric …
models (LLMs), specifically focusing on the abstraction of traditional and object-centric …
Advancements and challenges in object-centric process mining: a systematic literature review
Recent years have seen the emergence of object-centric process mining techniques. Born
as a response to the limitations of traditional process mining in analyzing event data from …
as a response to the limitations of traditional process mining in analyzing event data from …
Enhancing data-awareness of object-centric event logs
When multiple objects are involved in a process, there is an opportunity for processes to be
discovered from different angles with new information that previously might not have been …
discovered from different angles with new information that previously might not have been …
Object-centric alignments
Processes tend to interact with other processes and operate on various objects of different
types. These objects can influence each other creating dependencies between sub …
types. These objects can influence each other creating dependencies between sub …
Transforming event knowledge graph to object-centric event logs: A comparative study for multi-dimensional process analysis
Process mining has significantly transformed business process management by introducing
innovative data-based analysis techniques and empowering organizations to unveil hidden …
innovative data-based analysis techniques and empowering organizations to unveil hidden …
Preserving complex object-centric graph structures to improve machine learning tasks in process mining
Interactions of multiple processes and different objects can be captured using object-centric
event data. Object-centric event data represent process executions as event graphs of …
event data. Object-centric event data represent process executions as event graphs of …
[HTML][HTML] ocpa: A python library for object-centric process analysis
Abstract ocpa is a Python library supporting object-centric process mining. Traditional
process mining generates insights for one single process. However, many real-life …
process mining generates insights for one single process. However, many real-life …
Formulating the potentials of clustering of event data over multiple entities for decision support: a network embeddings approach
Event data from business processes evidence their patterns, behaviors, and dysfunctions.
Analytics techniques like clustering and sorting can reveal relevant insights, when data are …
Analytics techniques like clustering and sorting can reveal relevant insights, when data are …
Addressing convergence, divergence, and deficiency issues
JN Adams, WMP van der Aalst - International Conference on Business …, 2023 - Springer
The application of process mining algorithms to event logs requires the extraction of cases,
describing end-to-end runs through the process. When extracting cases for object-centric …
describing end-to-end runs through the process. When extracting cases for object-centric …