Graph-Based Clustering for Detecting Frequent Patterns in Event Log Data
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© 2016 IEEE. Finding frequent patterns is an important problem in data mining. We have devised a method for detecting frequent patterns in event log data. By representing events in a graph structure, we can generate clusters of frequently co-occurring events. This method is compared with basic association mining techniques and found to give a 'macro-level' overview of patterns, which is more interpretable. In addition, the resulting graph-based clustering output for frequently co-occurring event sets is substantially less than association mining, while providing similar information levels. Therefore, the results are more manageable for practical applications.
author list (cited authors)
Sy, E., Jacobs, S. A., Dagnino, A., & Ding, Y. u.