Embedding Graph Convolutional Networks in Recurrent Neural Networks for Predictive Monitoring
Predictive monitoring of business processes is a subfield of process mining that aims to predict, among other things, the characteristics of the next event or the sequence of next events. Although multiple approaches based on deep learning have been proposed, mainly recurrent neural networks and convolutional neural networks, none of them really exploit the structural information available in process models. This paper proposes an approach based on graph convolutional networks and recurrent neural networks that uses information directly from the process model. An experimental evaluation on real-life event logs shows that our approach is more consistent and outperforms the current state-of-the-art approaches.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Predictive Process Model Monitoring using Recurrent Neural Networks
The field of predictive process monitoring focuses on case-level models to predict a single specific outcome such as a particular objective, (remaining) time, or next activity/remaining sequence. Recently, a longer-horiz…
modelPredictive Process MonitoringTime Series AnalysisTime Series ForecastingPhysics-Guided Spatiotemporal Learning for Coastal Wave Peak Period Estimation from Video
Wave parameters in the nearshore are crucial for coastal engineering, shoreline protection, marine hazard assessment, and coastal management for climate resilience. Traditional monitoring systems like buoys and radar pla…
Period EstimationTransfer LearningAttention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting
Traffic forecasting is one of the most fundamental problems in transportation science and artificial intelligence. The key challenge is to effectively model complex spatial-temporal dependencies and correlations in moder…
Directly Follows Graphs Go Predictive Process Monitoring With Graph Neural Networks
In the past years, predictive process monitoring (PPM) techniques based on artificial neural networks have evolved as a method to monitor the future behavior of business processes. Existing approaches mostly focus on int…
Predictive Process MonitoringPredictive Process Monitoring Using Object-centric Graph Embeddings
Object-centric predictive process monitoring explores and utilizes object-centric event logs to enhance process predictions. The main challenge lies in extracting relevant information and building effective models. In th…
Activity Prediction