New publication for the International Conference on Process Mining: “Time-Aware LSTMs for Predictive Business Process Monitoring”
In the anticipation of the second International Conference on Process Mining (ICPM) our chair is delighted to introduce a new publication, which was written in cooperation with Machine Learning and Data Analytics Lab from FAU: “Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring”. In this paper An Nguyen, Srijeet Chatterjee, Sven Weinzierl, Leo Schwinn, Martin Matzner and Björn Eskofier propose a new predictive business process monitoring (PBPM) technique based on time-aware long short-term memory (T-LSTM) cells, which allows for better modelling of time dependencies between events. Furthermore, they introduce cost-sensitive learning to account for the common class imbalance in event logs.