Authors:
Li Kong
1
;
Chuanyi Li
1
;
Jidong Ge
1
;
Zhongjin Li
2
;
Feifei Zhang
1
and
Bin Luo
1
Affiliations:
1
State Key Laboratory for Novel Software Technology, Software Institute, Nanjing University, Nanjing 210093 and China
;
2
State Key Laboratory for Novel Software Technology, Software Institute, Nanjing University, Nanjing 210093, China, School of Computer, Hangzhou Dianzi University, Hangzhou 310018 and China
Keyword(s):
Log Repair, Process Mining, Event Log, Edit Distance.
Abstract:
Due to the big volume of data and complex execution, event logs of business processes inevitably contain various errors. In the field of process mining, if we derive process models from the event data without repairing, it is very likely that the resulting process is extremely different from what we expect. Current methods of repairing logs generally compare the log with an existing reference model to seek an optimal alignment, which requires that there should be a reliable reference model. Therefore, this paper presents an approach which only refers to the log itself to repair mistaken traces. We identify loop structures and frequent event sequences (sound conditions) between certain events. For each trace, basic trace and loop events are separated in advance. The basic trace is split into several parts to get repaired one by one according to sound conditions. Then loop events are added back and checked according to corresponding loop structure we discover. The repaired log should b
e as clean as possible and as similar to the original log as possible so that correctness and integrity of the original log are guaranteed. Experimental results based on different logs prove that our approach is effective and efficient.
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