Activity Mining for Airport Event Logs Based on RankClus Algorithm
XU Tao①② MENG Ye① LU Min①②
①(College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China) ②(Information Technology Research Base of Civil Aviation Administration of China, Tianjin 300300, China)
Process mining is a technology which can extract non-trivial and useful information from airport event logs. However, the airport event logs are always on a detailed level of abstraction, which may not be in line with the expected abstract level of an analyst. Process models generated by these event logs are always spaghetti-like and too hard to comprehend. An approach to overcome this issue is to group low-level events into clusters, which represent the execution of a higher-level activity in the process model. Therefore, this paper presents a new activity mining method which is based on RankClus algorithm to generate activity clusters integrated with ranking. On this basis, the activity-clustered model which is easier to comprehend can be constructed. The experiment results show that this activity-clustered model, which shares a similar level of conformance with the meta model, is significantly less complex.
徐涛, 孟野,卢敏. 基于RankClus算法的机场流程日志活动挖掘[J]. 电子与信息学报, 2016, 38(8): 2033-2039.
XU Tao, MENG Ye, LU Min . Activity Mining for Airport Event Logs Based on RankClus Algorithm. JEIT, 2016, 38(8): 2033-2039.
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