@article{10272/24653,
year = {2024},
url = {https://hdl.handle.net/10272/24653},
abstract = {Process mining is an efficient method that can analyze the full population of transactions
using the event log of business processes. Conventional rule-based process mining techniques can
detect anomalies; however, it tends to trigger a large number of false alarms. To improve the efficiency
of anomaly detection using process mining, this study adopts a deep learning-based classification
approach to detect anomalies in the traces of event logs. This approach contributes to the literature
by proposing a non-rule-based process mining technique based on deep learning. Results demonstrate
that the proposed non-rule-based process mining method can help auditors focus on transactional
anomalie},
publisher = {Universidad de Huelva},
title = {Applying deep learning to detect abnormal event log traces: a non-rule-based framework},
doi = {10.4192/1577-8517-v24_5},
author = {Wang, Yunsen and Chiu, Tiffany and Vasarhelyi, Miklos A.},
}