Correlation miner: mining business process models and causal relations without case identifiers

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Abstract

Process discovery algorithms aim to capture process models from event logs. These algorithms have been designed for logs in which the events that belong to the same case are related to each other — and to that case — by means of a unique case identifier. However, in service-oriented systems, these case identifiers are rarely stored beyond request-response pairs, which makes it hard to relate events that belong to the same case. This is known as the correlation challenge. This paper addresses the correlation challenge by introducing a technique, called the correlation miner, that facilitates discovery of business process models when events are not associated with a case identifier. It extends previous work on the correlation miner, by not only enabling the discovery of the process model, but also detecting which events belong to the same case. Experiments performed on both synthetic and real-world event logs show the applicability of the correlation miner. The resulting technique enables us to observe a service-oriented system and determine — with high accuracy — which request-response pairs sent by different communicating parties are related to each other.

Original languageEnglish
Article number1742002
Number of pages32
JournalInternational Journal of Cooperative Information Systems
Volume26
Issue number2
DOIs
Publication statusPublished - 1 Jun 2017

Keywords

  • Process mining
  • business process intelligence (BPI)
  • business process management (BPM)
  • event correlation
  • process discovery

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