In this paper we tackle the problem of next activity prediction/recommendation via "nested prediction model" learning, that is, we first identify recurrent and ...

This paper tackles the problem of next activity prediction/recommendation via "nested prediction model" learning, that is, it first identifies recurrent and ...

In this paper we tackle the problem of next activity prediction/recommendation via "nested prediction model" learning, that is, we first identify recurrent and ...

Distributed Learning of Process Models for Next Activity Prediction. https ... Completion time and next activity prediction of processes using sequential pattern ...

In this paper we tackle the problem of next activity prediction/recommendation via "nested prediction model" learning, that is, we first identify recurrent and ...

Jun 10, 2021 · Our goal is to show that we can significantly reduce the communication cost while keeping a decent convergence performance, compared to the ...

A hybrid framework of supervised/unsupervised machine learning methods is proposed to predict the outcomes of customers' experiences.

In this study, it was proposed the comparison of prediction performance of shallow learning algorithms with a three block Bidirectional LSTM (Bi-LSTM) ...

Mar 14, 2024 · Our research aims to investigate an algorithm with which semantic context in process event logs can be leveraged to predict the next activity in ...

Sep 27, 2024 · Deep learning models use PPM to predict future events and generate new traces. While empirical results show that discrete event simulation ...