Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive monitoring based on these techniques. However, the high disparity of process logs and experimental setups used to evaluate these approaches makes it especially difficult to make a fair comparison. Furthermore, it also difficults the selection of the most suitable approach to solve a specific problem. In this paper, we provide both a systematic literature review of approaches that use deep learning to tackle the predictive monitoring tasks. In addition, we performed an exhaustive experimental evaluation of 10 different approaches over 12 publicly available process logs.

翻译：对业务流程的预测性监测与对业务流程中持续案例的预测有关,最近,深层学习技术的普及促进了以这些技术为基础的预测性监测为核心的一套不断扩大的方法,然而,用于评价这些方法的流程日志和实验性设置差异很大,因此特别难以进行公平的比较,此外,也难以选择最合适的方法来解决具体问题。在本文件中,我们提供了对利用深层学习解决预测性监测任务的方法的系统文献审查。此外,我们还对12个公开可用的流程日志的10种不同方法进行了详尽的实验评价。