1. 事件日志的批量迹与过程模型的多视角对齐方法.
- Author
-
孙晋永, 邓文伟, 许 乾, and 孙志刚
- Subjects
- *
COST functions , *GENOME editing , *BATCH processing , *PROCESS mining , *PETRI nets , *PROBLEM solving , *MULTICASTING (Computer networks) - Abstract
In the consistency detection of business process discovery research, existing methods of multi-perspective alignment between event logs and process models can only obtain the optimal alignment of one trace with the process model at a time. Meanwhile the computation of heuristic function in obtaining the optimal alignment is complex, leading to low computation efficiency. To solve above problems, the paper proposed a multi-perspective alignment between batch traces of event log and process model based on trace minimum edit distance. Firstly, the study selected multiple traces in the event log to form batch traces, and used a process mining algorithm to obtain the log model of the batch traces. Then it obtained the product model of log model and process model and their transition system, which was the search space of batch traces. Then it designed a heuristic function based on the minimum edit distance between Petri net transition’s sequence set and the remaining traces to speed up the A* algorithm. Finally, the study designed a multi-perspective cost function that could adjust the weight of data and resource perspectives, and proposed a method of multi-perspective optimal alignment between each trace in the batch traces and the process model with the transition system of the product model. Compared with existing work, the simulation results show the proposed method takes up less memory space and uses less running time. This method improves the computation speed of heuristic function for optimal alignment, and obtains all optimal alignments of batch traces at one time, thus improves the efficiency of multi-perspective alignment between event logs and process models. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF