Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
A graph distance metric based on the maximal common subgraph
Pattern Recognition Letters
Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Process Mining: Discovering Direct Successors in Process Logs
DS '02 Proceedings of the 5th International Conference on Discovery Science
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
Matching and Merging of Statecharts Specifications
ICSE '07 Proceedings of the 29th international conference on Software Engineering
Rediscovering workflow models from event-based data using little thumb
Integrated Computer-Aided Engineering
Business alignment: using process mining as a tool for Delta analysis and conformance testing
Requirements Engineering
Delta analysis with workflow logs: aligning business process prescriptions and their reality
Requirements Engineering
Measuring Similarity between Business Process Models
CAiSE '08 Proceedings of the 20th international conference on Advanced Information Systems Engineering
ICMLA '09 Proceedings of the 2009 International Conference on Machine Learning and Applications
A hybrid approach for process mining: using from-to chart arranged by genetic algorithms
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
A visualization approach for difference analysis of process models and instance traffic
BPM'13 Proceedings of the 11th international conference on Business Process Management
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Business process management (BPM) continues to play a significant role in today's highly globalized world. In order to detect and prevent the gap between reference process model and the actual operation, process mining techniques discover operational model on the basis of the process logs. An important issue at BPM is to measure the similarity between the reference process model and discovered process model so that it can be possible to pinpoint where process participants deviate from the intended process description. In this paper, a hybrid quantitative approach is presented to measure the similarity between the process models. The proposed similarity metric is based on a hybrid process mining technique that makes use of genetic algorithms. The proposed approach itself is also a hybrid model that considers process activity dependencies and process structure.