References:
[1] Zeng QT. A Survey of Research Issues and Approaches on ProcessMining. Journal of System Simulation，2007, 19(s1): 275-280. (in Chinese with English abstract).
[2] Cook J E, Wolf A L. Discovering models of software processes fromevent-based data. ACM Transactions on Software Engineering and Methodology(TOSEM), 1998, 7(3): 215-249.
[3] Cabanillas C, Di Ciccio C, Mendling J, et al. Predictive task monitoringfor business processes. International Conference on Business ProcessManagement, 2014: 424-432.
[4] Maggi F M, Di Francescomarino C, Dumas M, et al. Predictive monitoringof business processes. International Conference on Advanced Information SystemsEngineering, 2014: 457-472.
[5] Breuker D, Matzner M, Delfmann P, et al. Comprehensible Predictive Modelsfor Business Processes. MIS Quarterly, 2016, 40(4)
[6] Evermann J, Rehse J-R, Fettke P. A deep learning approach forpredicting process behaviour at runtime. International Conference on BusinessProcess Management, 2016: 327-338.
[7] Tax N, Verenich I, La Rosa M, et al. Predictive business processmonitoring with LSTM neural networks. International Conference on AdvancedInformation Systems Engineering, 2017: 477-492.
附中文参考文献:
[1] 曾庆田. 过程挖掘的研究现状与问题综述.系统仿真学报, 2007,19(s1): 275-280.