Scientific paper resulting from the work of Elio Ribeiro Faria Junior. Published at the 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 4th International Conference on Process Mining (ICPM), titled “Clustering analysis and frequent pattern mining for process profile analysis: an exploratory study for object-centric event logs” and presented by Thais in the conference. The paper features collaboration from researchers MSc. Thais Rodrigues Neubauer, Prof. Dr. Marcelo Fantinato and Prof. Dr. Sarajane Marques Peres (Elio’s advisor).
Abstract: Object-centric event log is a format for properly organizing information from different views of a business process into an event log. The novelty in such a format is the association of events with objects, which allows different notions of cases to be analyzed. The addition of new features has brought an increase in complexity. Clustering analysis can ease this complexity by enabling the analysis to be guided by process behaviour profiles. However, identifying which features describe the singularity of each profile is a challenge. In this paper, we present an exploratory study in which we mine frequent patterns on top of clustering analysis as a mechanism for profile characterization. In our study, clustering analysis is applied in a trace clustering fashion over a vector representation for a flattened event log extracted from an object-centric event log, using a unique case notion. Then, frequent patterns are discovered in the event sublogs associated with clusters and organized according to that original object-centric event log. The results obtained in preliminary experiments show association rules reveal more evident behaviours in certain profiles. Despite the process underlying each cluster may contain the same elements (activities and transitions), the behaviour trends show the relationships between such elements are supposed to be different. The observations depicted in our analysis make room to search for subtler knowledge about the business process under scrutiny.
Complete paper here (Springer Link).
Reference: Faria Junior, E.R., Neubauer, T.R., Fantinato, M., Peres, S.M. (2023). Clustering Analysis and Frequent Pattern Mining for Process Profile Analysis: An Exploratory Study for Object-Centric Event Logs. In: Montali, M., Senderovich, A., Weidlich, M. (eds) Process Mining Workshops. ICPM 2022. Lecture Notes in Business Information Processing, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-27815-0_20
Bibtex:
@InProceedings{FariaJunior2022,
author=”Faria Junior, Elio Ribeiro and Neubauer, Thais Rodrigues and Fantinato, Marcelo and Peres, Sarajane Marques”,
editor=”Montali, Marco
and Senderovich, Arik
and Weidlich, Matthias”,
title=”Clustering Analysis and Frequent Pattern Mining for Process Profile Analysis: An Exploratory Study for Object-Centric Event Logs”,
booktitle=”Process Mining Workshops”,
year=”2023″,
publisher=”Springer Nature Switzerland”,
address=”Cham”,
pages=”269–281″,
isbn=”978-3-031-27815-0″
}
Artigo científico resultante do trabalho de Elio Ribeiro Faria Junior. Publicado no 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) – 4th International Conference on Process Mining (ICPM), intitulado “Clustering analysis and frequent pattern mining for process profile analysis: an exploratory study for object-centric event logs” e apresentado por Thais na conferência. O paper conta com a colaboração de MSc. Thais Rodrigues Neubauer, Prof. Dr. Marcelo Fantinato and Profa. Dra. Sarajane Marques Peres (orientadora).
Artigo completo aqui – em inglês (Springer Link).
Referência: Faria Junior, E.R., Neubauer, T.R., Fantinato, M., Peres, S.M. (2023). Clustering Analysis and Frequent Pattern Mining for Process Profile Analysis: An Exploratory Study for Object-Centric Event Logs. In: Montali, M., Senderovich, A., Weidlich, M. (eds) Process Mining Workshops. ICPM 2022. Lecture Notes in Business Information Processing, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-27815-0_20
Bibtex:
@InProceedings{FariaJunior2022,
author=”Faria Junior, Elio Ribeiro and Neubauer, Thais Rodrigues and Fantinato, Marcelo and Peres, Sarajane Marques”,
editor=”Montali, Marco
and Senderovich, Arik
and Weidlich, Matthias”,
title=”Clustering Analysis and Frequent Pattern Mining for Process Profile Analysis: An Exploratory Study for Object-Centric Event Logs”,
booktitle=”Process Mining Workshops”,
year=”2023″,
publisher=”Springer Nature Switzerland”,
address=”Cham”,
pages=”269–281″,
isbn=”978-3-031-27815-0″
}
