On Systematic Approach to Discovering Periodic Patterns in Event Logs
Discovering periodic patterns from historical information is a computationally hard problem due to the large amounts of historical data to be analyzed and due to a high complexity of the patterns. This work shows how the derivations rules for periodic patterns can be applied to discover complex patterns in case of logs of events. The paper defines a concept of periodic pattern and its validation in a workload trace created from the logs of events. A system of derivations rules that transforms periodic patterns into the logically equivalent ones is proposed. The paper presents a systematic approach based on the system of derivation rules to discovery of periodic patterns in logs of events.
KeywordsPeriodic Pattern Composition Rule Discovery Rule Derivation Rule Split Rule
- 1.Van der Aalst, W.M.P.: Process Mining Discovery, Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)Google Scholar
- 4.Özden, B., Ramaswamy, S., Silberschatz, A.: Cyclic association rules. In: Proceedings of the Fourteenth International Conference on Data Engineering, pp. 412–421 (1998)Google Scholar
- 7.Yeh, J.S., Lin, S.C., Hu, S.C.: Novel algorithms for asynchronous periodic pattern mining based on 2-d linked list. Int. J. Database Theory Appl. 5(4), 33–43 (2012)Google Scholar
- 8.Getta, J., Zimniak, M., Benn, W.: Mining periodic patterns from nested event logs. In: The 14th IEEE International Conference on Computer and Information Technology, CIT 2014, pp. 160–167 (2014)Google Scholar