Process model matching provides the basis for many process analysis techniques such as inconsistency detection and process querying. The matching task refers to the automatic identification of correspondences between activities in two process models. Numerous techniques have been developed for this purpose, all share a focus on process-level information. In this paper we introduce instance-based process matching, which specifically focuses on information related to instances of a process. In particular, we introduce six similarity metrics that each use a different type of instance information stored in the event logs associated with processes. The proposed metrics can be used as standalone matching techniques or to complement existing process model matching techniques. A quantitative evaluation on real-world data demonstrates that the use of information from event logs is essential in identifying a considerable amount of correspondences.
|Title of host publication||Advanced Information Systems Engineering - 29th International Conference, CAiSE 2017|
|Editors||Eric Dubois, Klaus Pohl|
|Number of pages||15|
|Publication status||Published - 2017|
|Event||Forum and Doctoral Consortium Papers Presented at the 29th International Conference on Advanced Information Systems Engineering, CAiSE-Forum-DC 2017 - Essen, Germany|
Duration: 12 Jun 2017 → 16 Jun 2017
|Conference||Forum and Doctoral Consortium Papers Presented at the 29th International Conference on Advanced Information Systems Engineering, CAiSE-Forum-DC 2017|
|Period||12/06/2017 → 16/06/2017|
|Series||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
Bibliographical notePublisher Copyright:
© Springer International Publishing AG 2017.
- Event logs
- Process model matching
- Process similarity