Explainable Business Process Remaining Time Prediction Using Reachability Graph
نویسندگان
چکیده
With the recent advances in field of deep learning, an increasing number neural networks have been applied to business process prediction tasks, remaining time prediction, obtain more accurate predictive results. However, existing methods based on learning poor interpretability, explainable method is proposed using reachability graph, which consists model construction and visualization. For models, a Petri net mined graph constructed transition occurrence vector. Then, prefixes corresponding suffixes are generated cluster into different partitions according Next, bidirectional recurrent network with attention each partition encode prefixes, transfer between performed. visualization evaluation values added sub-processes realize models. Finally, validated by publicly available event logs.
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ژورنال
عنوان ژورنال: Chinese Journal of Electronics
سال: 2023
ISSN: ['1022-4653', '2075-5597']
DOI: https://doi.org/10.23919/cje.2021.00.170