Predicting process behavior meets factorization machines

作者：

Highlights：

• Easy-to-configure model to predict the next event of ongoing cases in a process.

• Cases are represented as overlapping steps to include sequential information.

• Model training with negative feedback information improves prediction precision.

• Experiments show performance comparable to state-of-the-art techniques.

摘要

•Easy-to-configure model to predict the next event of ongoing cases in a process.•Cases are represented as overlapping steps to include sequential information.•Model training with negative feedback information improves prediction precision.•Experiments show performance comparable to state-of-the-art techniques.

论文关键词：Recommender systems,Business process management,Predictive business process monitoring

论文评审过程：Received 4 March 2018, Revised 3 May 2018, Accepted 25 May 2018, Available online 30 May 2018, Version of Record 26 June 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.05.035