Activity Mining for Airport Event Logs Based on RankClus Algorithm

XU Tao; MENG Ye; LU Min

doi:10.11999/JEIT151137

Volume 38 Issue 8

Sep. 2016

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XU Tao, MENG Ye, LU Min . Activity Mining for Airport Event Logs Based on RankClus Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2033-2039. doi: 10.11999/JEIT151137

Citation:

XU Tao, MENG Ye, LU Min . Activity Mining for Airport Event Logs Based on RankClus Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2033-2039. doi: 10.11999/JEIT151137

XU Tao, MENG Ye, LU Min . Activity Mining for Airport Event Logs Based on RankClus Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2033-2039. doi: 10.11999/JEIT151137

Citation:

XU Tao, MENG Ye, LU Min . Activity Mining for Airport Event Logs Based on RankClus Algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(8): 2033-2039. doi: 10.11999/JEIT151137

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Activity Mining for Airport Event Logs Based on RankClus Algorithm

doi: 10.11999/JEIT151137 cstr: 32379.14.JEIT151137

XU Tao¹,
MENG Ye²,
LU Min ¹

1.
2.
(College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China)

Funds:

The National Natural Science Foundation of China (61502499), The Civil Aviation Key Technologies RD Program of China (MHRD20140105), The Fundamental Research Funds for the Central Universities of China (3122013C005, 3122014D032, 3122015D015), The Scientific Research Foundation from Civil Aviation University of China (2013QD18X), The Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China (CAAC-ITRB-201401)

Received Date: 2015-10-10
Rev Recd Date: 2016-04-15
Publish Date: 2016-08-19

Abstract

Abstract

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.
- Process mining,
- Activity mining,
- RankClus,
- Trace clustering

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References(20)

References

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